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<font color="#ffffff" face="helvetica, arial"> <br><big><big><strong><a href="matplotlib.html"><font color="#ffffff">matplotlib</font></a>.axes</strong></big></big></font></td
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><font color="#ffffff" face="helvetica, arial"><a href=".">index</a><br><a href="file:/home/jdhunter/dev/lib/python2.5/site-packages/matplotlib/axes.py">/home/jdhunter/dev/lib/python2.5/site-packages/matplotlib/axes.py</a></font></td></tr></table>
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<td width="100%"><dl>
<dt><font face="helvetica, arial"><a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>
</font></dt><dd>
<dl>
<dt><font face="helvetica, arial"><a href="matplotlib.axes.html#Axes">Axes</a>
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<dl>
<dt><font face="helvetica, arial"><a href="matplotlib.axes.html#PolarAxes">PolarAxes</a>
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<dt><font face="helvetica, arial"><a href="matplotlib.axes.html#SubplotBase">SubplotBase</a>
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<dt><font face="helvetica, arial"><a href="matplotlib.axes.html#PolarSubplot">PolarSubplot</a>(<a href="matplotlib.axes.html#SubplotBase">SubplotBase</a>, <a href="matplotlib.axes.html#PolarAxes">PolarAxes</a>)
</font></dt><dt><font face="helvetica, arial"><a href="matplotlib.axes.html#Subplot">Subplot</a>(<a href="matplotlib.axes.html#SubplotBase">SubplotBase</a>, <a href="matplotlib.axes.html#Axes">Axes</a>)
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<p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#ffc8d8">
<td colspan=3 valign=bottom> <br>
<font color="#000000" face="helvetica, arial"><a name="Axes">class <strong>Axes</strong></a>(<a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>)</font></td></tr>
<tr bgcolor="#ffc8d8"><td rowspan=2><tt> </tt></td>
<td colspan=2><tt>The <a href="#Axes">Axes</a> contains most of the figure elements: Axis, Tick, Line2D,<br>
Text, Polygon etc, and sets the coordinate system<br> </tt></td></tr>
<tr><td> </td>
<td width="100%">Methods defined here:<br>
<dl><dt><a name="Axes-__init__"><strong>__init__</strong></a>(self, fig, rect, axisbg<font color="#909090">=None</font>, frameon<font color="#909090">=True</font>, sharex<font color="#909090">=None</font>, sharey<font color="#909090">=None</font>, label<font color="#909090">=''</font>, **kwargs)</dt><dd><tt>Build an <a href="#Axes">Axes</a> instance in Figure with<br>
rect=[left, bottom, width,height in Figure coords<br>
<br>
adjustable: ['box' | 'datalim']<br>
alpha: the alpha transparency<br>
anchor: ['C', 'SW', 'S', 'SE', 'E', 'NE', 'N', 'NW', 'W']<br>
aspect: ['auto' | 'equal' | aspect_ratio]<br>
autoscale_on: boolean - whether or not to autoscale the viewlim<br>
axis_bgcolor: any matplotlib color - see help(colors)<br>
axisbelow: draw the grids and ticks below the other artists<br>
cursor_props: a (float, color) tuple<br>
figure: a Figure instance<br>
frame_on: a boolean - draw the axes frame<br>
label: the axes label<br>
navigate: True|False<br>
navigate_mode: the navigation toolbar button status: 'PAN', 'ZOOM', or None<br>
position: [left, bottom, width,height in Figure coords<br>
sharex : an <a href="#Axes">Axes</a> instance to share the x-axis with<br>
sharey : an <a href="#Axes">Axes</a> instance to share the y-axis with<br>
title: the title string<br>
visible: a boolean - whether the axes is visible<br>
xlabel: the xlabel<br>
xlim: (xmin, xmax) view limits<br>
xscale: ['log' | 'linear' ]<br>
xticklabels: sequence of strings<br>
xticks: sequence of floats<br>
ylabel: the ylabel strings<br>
ylim: (ymin, ymax) view limits<br>
yscale: ['log' | 'linear']<br>
yticklabels: sequence of strings<br>
yticks: sequence of floats</tt></dd></dl>
<dl><dt><a name="Axes-acorr"><strong>acorr</strong></a>(self, x, **kwargs)</dt><dd><tt>ACORR(x, normed=False, detrend=detrend_none, usevlines=False,<br>
maxlags=None, **kwargs)<br>
Plot the autocorrelation of x. If normed=True, normalize the<br>
data but the autocorrelation at 0-th lag. x is detrended by<br>
the detrend callable (default no normalization.<br>
data are plotted as <a href="#Axes-plot">plot</a>(lags, c, **kwargs)<br>
return value is lags, c, line where lags are a length<br>
2*maxlags+1 lag vector, c is the 2*maxlags+1 auto correlation<br>
vector, and line is a Line2D instance returned by plot. The<br>
default linestyle is None and the default marker is 'o',<br>
though these can be overridden with keyword args. The cross<br>
correlation is performed with numerix cross_correlate with<br>
mode=2.<br>
If usevlines is True, <a href="#Axes">Axes</a>.vlines rather than <a href="#Axes">Axes</a>.plot is used<br>
to draw vertical lines from the origin to the acorr.<br>
Otherwise the plotstyle is determined by the kwargs, which are<br>
Line2D properties. If usevlines, the return value is lags, c,<br>
linecol, b where linecol is the LineCollection and b is the x-axis<br>
if usevlines=True, kwargs are passed onto <a href="#Axes">Axes</a>.vlines<br>
if usevlines=False, kwargs are passed onto <a href="#Axes">Axes</a>.plot<br>
maxlags is a positive integer detailing the number of lags to show.<br>
The default value of None will return all (2*len(x)-1) lags.<br>
See the respective function for documentation on valid kwargs</tt></dd></dl>
<dl><dt><a name="Axes-add_artist"><strong>add_artist</strong></a>(self, a)</dt><dd><tt>Add any artist to the axes</tt></dd></dl>
<dl><dt><a name="Axes-add_collection"><strong>add_collection</strong></a>(self, collection, autolim<font color="#909090">=False</font>)</dt><dd><tt>add a Collection instance to <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="Axes-add_line"><strong>add_line</strong></a>(self, line)</dt><dd><tt>Add a line to the list of plot lines</tt></dd></dl>
<dl><dt><a name="Axes-add_patch"><strong>add_patch</strong></a>(self, p)</dt><dd><tt>Add a patch to the list of <a href="#Axes">Axes</a> patches; the clipbox will be<br>
set to the <a href="#Axes">Axes</a> clipping box. If the transform is not set, it<br>
wil be set to self.<strong>transData</strong>.</tt></dd></dl>
<dl><dt><a name="Axes-add_table"><strong>add_table</strong></a>(self, tab)</dt><dd><tt>Add a table instance to the list of axes tables</tt></dd></dl>
<dl><dt><a name="Axes-annotate"><strong>annotate</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#Axes-annotate">annotate</a>(self, s, xy, textloc,<br>
xycoords='data', textcoords='data',<br>
lineprops=None,<br>
markerprops=None<br>
**props)<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-apply_aspect"><strong>apply_aspect</strong></a>(self, data_ratio<font color="#909090">=None</font>)</dt><dd><tt>Use self.<strong>_aspect</strong> and self.<strong>_adjustable</strong> to modify the<br>
axes box or the view limits.<br>
The data_ratio kwarg is set to 1 for polar axes. It is<br>
used only when _adjustable is 'box'.</tt></dd></dl>
<dl><dt><a name="Axes-arrow"><strong>arrow</strong></a>(self, x, y, dx, dy, **kwargs)</dt><dd><tt>Draws arrow on specified axis from (x,y) to (x+dx,y+dy).<br>
Optional kwargs control the arrow properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-autoscale_view"><strong>autoscale_view</strong></a>(self, tight<font color="#909090">=False</font>, scalex<font color="#909090">=True</font>, scaley<font color="#909090">=True</font>)</dt><dd><tt>autoscale the view limits using the data limits. You can<br>
selectively autoscale only a single axis, eg, the xaxis by<br>
setting scaley to False. The autoscaling preserves any<br>
axis direction reversal that has already been done.</tt></dd></dl>
<dl><dt><a name="Axes-axhline"><strong>axhline</strong></a>(self, y<font color="#909090">=0</font>, xmin<font color="#909090">=0</font>, xmax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXHLINE(y=0, xmin=0, xmax=1, **kwargs)<br>
Axis Horizontal Line<br>
Draw a horizontal line at y from xmin to xmax. With the default<br>
values of xmin=0 and xmax=1, this line will always span the horizontal<br>
extent of the axes, regardless of the xlim settings, even if you<br>
change them, eg with the xlim command. That is, the horizontal extent<br>
is in axes coords: 0=left, 0.5=middle, 1.0=right but the y location is<br>
in data coordinates.<br>
Return value is the Line2D instance. kwargs are the same as kwargs to<br>
plot, and can be used to control the line properties. Eg<br>
# draw a thick red hline at y=0 that spans the xrange<br>
<a href="#Axes-axhline">axhline</a>(linewidth=4, color='r')<br>
# draw a default hline at y=1 that spans the xrange<br>
<a href="#Axes-axhline">axhline</a>(y=1)<br>
# draw a default hline at y=.5 that spans the the middle half of<br>
# the xrange<br>
<a href="#Axes-axhline">axhline</a>(y=.5, xmin=0.25, xmax=0.75)<br>
Valid kwargs are Line2D properties<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-axhspan"><strong>axhspan</strong></a>(self, ymin, ymax, xmin<font color="#909090">=0</font>, xmax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXHSPAN(ymin, ymax, xmin=0, xmax=1, **kwargs)<br>
Axis Horizontal Span. ycoords are in data units and x<br>
coords are in axes (relative 0-1) units<br>
Draw a horizontal span (regtangle) from ymin to ymax. With the<br>
default values of xmin=0 and xmax=1, this always span the xrange,<br>
regardless of the xlim settings, even if you change them, eg with the<br>
xlim command. That is, the horizontal extent is in axes coords:<br>
0=left, 0.5=middle, 1.0=right but the y location is in data<br>
coordinates.<br>
kwargs are the kwargs to Patch, eg<br>
antialiased, aa<br>
linewidth, lw<br>
edgecolor, ec<br>
facecolor, fc<br>
the terms on the right are aliases<br>
Return value is the patches.Polygon instance.<br>
#draws a gray rectangle from y=0.25-0.75 that spans the horizontal<br>
#extent of the axes<br>
<a href="#Axes-axhspan">axhspan</a>(0.25, 0.75, facecolor='0.5', alpha=0.5)<br>
Valid kwargs are Polygon properties<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-axis"><strong>axis</strong></a>(self, *v, **kwargs)</dt><dd><tt>Convenience method for manipulating the x and y view limits<br>
and the aspect ratio of the plot.<br>
<br>
kwargs are passed on to set_xlim and set_ylim -- see their docstrings for details</tt></dd></dl>
<dl><dt><a name="Axes-axvline"><strong>axvline</strong></a>(self, x<font color="#909090">=0</font>, ymin<font color="#909090">=0</font>, ymax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXVLINE(x=0, ymin=0, ymax=1, **kwargs)<br>
Axis Vertical Line<br>
Draw a vertical line at x from ymin to ymax. With the default values<br>
of ymin=0 and ymax=1, this line will always span the vertical extent<br>
of the axes, regardless of the xlim settings, even if you change them,<br>
eg with the xlim command. That is, the vertical extent is in axes<br>
coords: 0=bottom, 0.5=middle, 1.0=top but the x location is in data<br>
coordinates.<br>
Return value is the Line2D instance. kwargs are the same as<br>
kwargs to plot, and can be used to control the line properties. Eg<br>
# draw a thick red vline at x=0 that spans the yrange<br>
l = <a href="#Axes-axvline">axvline</a>(linewidth=4, color='r')<br>
# draw a default vline at x=1 that spans the yrange<br>
l = <a href="#Axes-axvline">axvline</a>(x=1)<br>
# draw a default vline at x=.5 that spans the the middle half of<br>
# the yrange<br>
<a href="#Axes-axvline">axvline</a>(x=.5, ymin=0.25, ymax=0.75)<br>
Valid kwargs are Line2D properties<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-axvspan"><strong>axvspan</strong></a>(self, xmin, xmax, ymin<font color="#909090">=0</font>, ymax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXVSPAN(xmin, xmax, ymin=0, ymax=1, **kwargs)<br>
axvspan : Axis Vertical Span. xcoords are in data units and y coords<br>
are in axes (relative 0-1) units<br>
Draw a vertical span (regtangle) from xmin to xmax. With the default<br>
values of ymin=0 and ymax=1, this always span the yrange, regardless<br>
of the ylim settings, even if you change them, eg with the ylim<br>
command. That is, the vertical extent is in axes coords: 0=bottom,<br>
0.5=middle, 1.0=top but the y location is in data coordinates.<br>
kwargs are the kwargs to Patch, eg<br>
antialiased, aa<br>
linewidth, lw<br>
edgecolor, ec<br>
facecolor, fc<br>
the terms on the right are aliases<br>
return value is the patches.Polygon instance.<br>
# draw a vertical green translucent rectangle from x=1.25 to 1.55 that<br>
# spans the yrange of the axes<br>
<a href="#Axes-axvspan">axvspan</a>(1.25, 1.55, facecolor='g', alpha=0.5)<br>
Valid kwargs are Polygon properties<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-bar"><strong>bar</strong></a>(self, left, height, width<font color="#909090">=0.80000000000000004</font>, bottom<font color="#909090">=None</font>, color<font color="#909090">=None</font>, edgecolor<font color="#909090">=None</font>, linewidth<font color="#909090">=None</font>, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, ecolor<font color="#909090">=None</font>, capsize<font color="#909090">=3</font>, align<font color="#909090">='edge'</font>, orientation<font color="#909090">='vertical'</font>, log<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>BAR(left, height, width=0.8, bottom=0,<br>
color=None, edgecolor=None, linewidth=None,<br>
yerr=None, xerr=None, ecolor=None, capsize=3,<br>
align='edge', orientation='vertical', log=False)<br>
Make a bar plot with rectangles bounded by<br>
left, left+width, bottom, bottom+height<br>
(left, right, bottom and top edges)<br>
left, height, width, and bottom can be either scalars or sequences<br>
Return value is a list of Rectangle patch instances<br>
left - the x coordinates of the left sides of the bars<br>
height - the heights of the bars<br>
Optional arguments:<br>
width - the widths of the bars<br>
bottom - the y coordinates of the bottom edges of the bars<br>
color - the colors of the bars<br>
edgecolor - the colors of the bar edges<br>
linewidth - width of bar edges; None means use default<br>
linewidth; 0 means don't draw edges.<br>
xerr and yerr, if not None, will be used to generate errorbars<br>
on the bar chart<br>
ecolor specifies the color of any errorbar<br>
capsize (default 3) determines the length in points of the error<br>
bar caps<br>
align = 'edge' (default) | 'center'<br>
orientation = 'vertical' | 'horizontal'<br>
log = False | True - False (default) leaves the orientation<br>
axis as-is; True sets it to log scale<br>
For vertical bars, align='edge' aligns bars by their left edges in<br>
left, while 'center' interprets these values as the x coordinates of<br>
the bar centers. For horizontal bars, 'edge' aligns bars by their<br>
bottom edges in bottom, while 'center' interprets these values as the<br>
y coordinates of the bar centers.<br>
The optional arguments color, edgecolor, linewidth, xerr, and yerr can<br>
be either scalars or sequences of length equal to the number of bars.<br>
This enables you to use bar as the basis for stacked bar charts, or<br>
candlestick plots.<br>
Optional kwargs:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-barh"><strong>barh</strong></a>(self, bottom, width, height<font color="#909090">=0.80000000000000004</font>, left<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>BARH(bottom, width, height=0.8, left=0, **kwargs)<br>
Make a horizontal bar plot with rectangles bounded by<br>
left, left+width, bottom, bottom+height<br>
(left, right, bottom and top edges)<br>
bottom, width, height, and left can be either scalars or sequences<br>
Return value is a list of Rectangle patch instances<br>
bottom - the vertical positions of the bottom edges of the bars<br>
width - the lengths of the bars<br>
Optional arguments:<br>
height - the heights (thicknesses) of the bars<br>
left - the x coordinates of the left edges of the bars<br>
color - the colors of the bars<br>
edgecolor - the colors of the bar edges<br>
linewidth - width of bar edges; None means use default<br>
linewidth; 0 means don't draw edges.<br>
xerr and yerr, if not None, will be used to generate errorbars<br>
on the bar chart<br>
ecolor specifies the color of any errorbar<br>
capsize (default 3) determines the length in points of the error<br>
bar caps<br>
align = 'edge' (default) | 'center'<br>
log = False | True - False (default) leaves the horizontal<br>
axis as-is; True sets it to log scale<br>
Setting align='edge' aligns bars by their bottom edges in bottom,<br>
while 'center' interprets these values as the y coordinates of the bar<br>
centers.<br>
The optional arguments color, edgecolor, linewidth, xerr, and yerr can<br>
be either scalars or sequences of length equal to the number of bars.<br>
This enables you to use barh as the basis for stacked bar charts, or<br>
candlestick plots.<br>
Optional kwargs:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-boxplot"><strong>boxplot</strong></a>(self, x, notch<font color="#909090">=0</font>, sym<font color="#909090">='b+'</font>, vert<font color="#909090">=1</font>, whis<font color="#909090">=1.5</font>, positions<font color="#909090">=None</font>, widths<font color="#909090">=None</font>)</dt><dd><tt><a href="#Axes-boxplot">boxplot</a>(x, notch=0, sym='+', vert=1, whis=1.5,<br>
positions=None, widths=None)<br>
<br>
Make a box and whisker plot for each column of x or<br>
each vector in sequence x.<br>
The box extends from the lower to upper quartile values<br>
of the data, with a line at the median. The whiskers<br>
extend from the box to show the range of the data. Flier<br>
points are those past the end of the whiskers.<br>
<br>
notch = 0 (default) produces a rectangular box plot.<br>
notch = 1 will produce a notched box plot<br>
<br>
sym (default 'b+') is the default symbol for flier points.<br>
Enter an empty string ('') if you don't want to show fliers.<br>
<br>
vert = 1 (default) makes the boxes vertical.<br>
vert = 0 makes horizontal boxes. This seems goofy, but<br>
that's how Matlab did it.<br>
<br>
whis (default 1.5) defines the length of the whiskers as<br>
a function of the inner quartile range. They extend to the<br>
most extreme data point within ( whis*(75%-25%) ) data range.<br>
<br>
positions (default 1,2,...,n) sets the horizontal positions of<br>
the boxes. The ticks and limits are automatically set to match<br>
the positions.<br>
<br>
widths is either a scalar or a vector and sets the width of<br>
each box. The default is 0.5, or 0.15*(distance between extreme<br>
positions) if that is smaller.<br>
<br>
x is an array or a sequence of vectors.<br>
<br>
Returns a list of the lines added.</tt></dd></dl>
<dl><dt><a name="Axes-broken_barh"><strong>broken_barh</strong></a>(self, xranges, yrange, **kwargs)</dt><dd><tt>A collection of horizontal bars spanning yrange with a sequence of<br>
xranges<br>
xranges : sequence of (xmin, xwidth)<br>
yrange : (ymin, ywidth)<br>
kwargs are collections.BrokenBarHCollection properties<br>
alpha: float<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
edgecolor: matplotlib color arg or sequence of rgba tuples<br>
facecolor: matplotlib color arg or sequence of rgba tuples<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number<br>
these can either be a single argument, ie facecolors='black'<br>
or a sequence of arguments for the various bars, ie<br>
facecolors='black', 'red', 'green'</tt></dd></dl>
<dl><dt><a name="Axes-cla"><strong>cla</strong></a>(self)</dt><dd><tt>Clear the current axes</tt></dd></dl>
<dl><dt><a name="Axes-clabel"><strong>clabel</strong></a>(self, CS, *args, **kwargs)</dt><dd><tt><a href="#Axes-clabel">clabel</a>(CS, **kwargs) - add labels to line contours in CS,<br>
where CS is a ContourSet object returned by contour.<br>
<br>
<a href="#Axes-clabel">clabel</a>(CS, V, **kwargs) - only label contours listed in V<br>
<br>
keyword arguments:<br>
<br>
* fontsize = None: as described in <a href="http://matplotlib.sf.net/fonts.html">http://matplotlib.sf.net/fonts.html</a><br>
<br>
* colors = None:<br>
<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different labels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all labels<br>
will be plotted in this color<br>
<br>
- if colors == None, the color of each label matches the color<br>
of the corresponding contour<br>
<br>
* inline = True: controls whether the underlying contour is removed<br>
(inline = True) or not (False)<br>
<br>
* fmt = '%1.3f': a format string for the label</tt></dd></dl>
<dl><dt><a name="Axes-clear"><strong>clear</strong></a>(self)</dt><dd><tt>clear the axes</tt></dd></dl>
<dl><dt><a name="Axes-cohere"><strong>cohere</strong></a>(self, x, y, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, window<font color="#909090">=<function window_hanning at 0xb5bc7764></font>, noverlap<font color="#909090">=0</font>, **kwargs)</dt><dd><tt>COHERE(x, y, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0, **kwargs)<br>
cohere the coherence between x and y. Coherence is the normalized<br>
cross spectral density<br>
Cxy = |Pxy|^2/(Pxx*Pyy)<br>
The return value is (Cxy, f), where f are the frequencies of the<br>
coherence vector.<br>
See the PSD help for a description of the optional parameters.<br>
kwargs are applied to the lines<br>
Returns the tuple Cxy, freqs<br>
Refs: Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)<br>
kwargs control the Line2D properties of the coherence plot:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-connect"><strong>connect</strong></a>(self, s, func)</dt><dd><tt>Register observers to be notified when certain events occur. Register<br>
with callback functions with the following signatures. The function<br>
has the following signature<br>
<br>
func(ax) # where ax is the instance making the callback.<br>
<br>
The following events can be connected to:<br>
<br>
'xlim_changed','ylim_changed'<br>
<br>
The connection id is is returned - you can use this with<br>
disconnect to disconnect from the axes event</tt></dd></dl>
<dl><dt><a name="Axes-contour"><strong>contour</strong></a>(self, *args, **kwargs)</dt><dd><tt>contour and contourf draw contour lines and filled contours,<br>
respectively. Except as noted, function signatures and return<br>
values are the same for both versions.<br>
<br>
contourf differs from the Matlab (TM) version in that it does not<br>
draw the polygon edges, because the contouring engine yields<br>
simply connected regions with branch cuts. To draw the edges,<br>
add line contours with calls to contour.<br>
<br>
<br>
Function signatures<br>
<br>
<a href="#Axes-contour">contour</a>(Z) - make a contour plot of an array Z. The level<br>
values are chosen automatically.<br>
<br>
<a href="#Axes-contour">contour</a>(X,Y,Z) - X,Y specify the (x,y) coordinates of the surface<br>
<br>
<a href="#Axes-contour">contour</a>(Z,N) and <a href="#Axes-contour">contour</a>(X,Y,Z,N) - contour N automatically-chosen<br>
levels.<br>
<br>
<a href="#Axes-contour">contour</a>(Z,V) and <a href="#Axes-contour">contour</a>(X,Y,Z,V) - draw len(V) contour lines,<br>
at the values specified in sequence V<br>
<br>
<a href="#Axes-contourf">contourf</a>(..., V) - fill the (len(V)-1) regions between the<br>
values in V<br>
<br>
<a href="#Axes-contour">contour</a>(Z, **kwargs) - Use keyword args to control colors, linewidth,<br>
origin, cmap ... see below<br>
<br>
X, Y, and Z must be arrays with the same dimensions.<br>
Z may be a masked array, but filled contouring may not handle<br>
internal masked regions correctly.<br>
<br>
C = <a href="#Axes-contour">contour</a>(...) returns a ContourSet object.<br>
<br>
<br>
Optional keyword args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* colors = None; or one of the following:<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different levels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all levels<br>
will be plotted in this color<br>
<br>
- if colors == None, the colormap specified by cmap will be used<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
* cmap = None: a cm Colormap instance from matplotlib.cm.<br>
- if cmap == None and colors == None, a default Colormap is used.<br>
<br>
* norm = None: a matplotlib.colors.Normalize instance for<br>
scaling data values to colors.<br>
- if norm == None, and colors == None, the default<br>
linear scaling is used.<br>
<br>
* origin = None: 'upper'|'lower'|'image'|None.<br>
If 'image', the rc value for image.origin will be used.<br>
If None (default), the first value of Z will correspond<br>
to the lower left corner, location (0,0).<br>
This keyword is active only if contourf is called with<br>
one or two arguments, that is, without explicitly<br>
specifying X and Y.<br>
<br>
* extent = None: (x0,x1,y0,y1); also active only if X and Y<br>
are not specified. If origin is not None, then extent is<br>
interpreted as in imshow: it gives the outer pixel boundaries.<br>
In this case, the position of Z[0,0] is the center of the<br>
pixel, not a corner.<br>
If origin is None, then (x0,y0) is the position of Z[0,0],<br>
and (x1,y1) is the position of Z[-1,-1].<br>
<br>
* locator = None: an instance of a ticker.Locator subclass;<br>
default is MaxNLocator. It is used to determine the<br>
contour levels if they are not given explicitly via the<br>
V argument.<br>
<br>
***** New: *****<br>
* extend = 'neither', 'both', 'min', 'max'<br>
Unless this is 'neither' (default), contour levels are<br>
automatically added to one or both ends of the range so that<br>
all data are included. These added ranges are then<br>
mapped to the special colormap values which default to<br>
the ends of the colormap range, but can be set via<br>
Colormap.set_under() and Colormap.set_over() methods.<br>
To replace clip_ends=True and V = [-100, 2, 1, 0, 1, 2, 100],<br>
use extend='both' and V = [2, 1, 0, 1, 2].<br>
****************<br>
<br>
contour only:<br>
* linewidths = None: or one of these:<br>
- a number - all levels will be plotted with this linewidth,<br>
e.g. linewidths = 0.6<br>
<br>
- a tuple of numbers, e.g. linewidths = (0.4, 0.8, 1.2) different<br>
levels will be plotted with different linewidths in the order<br>
specified<br>
<br>
- if linewidths == None, the default width in lines.linewidth in<br>
matplotlibrc is used<br>
<br>
contourf only:<br>
***** Obsolete: ****<br>
* clip_ends = True<br>
If False, the limits for color scaling are set to the<br>
minimum and maximum contour levels.<br>
True (default) clips the scaling limits. Example:<br>
if the contour boundaries are V = [-100, 2, 1, 0, 1, 2, 100],<br>
then the scaling limits will be [-100, 100] if clip_ends<br>
is False, and [-3, 3] if clip_ends is True.<br>
* linewidths = None or a number; default of 0.05 works for<br>
Postscript; a value of about 0.5 seems better for Agg.<br>
* antialiased = True (default) or False; if False, there is<br>
no need to increase the linewidths for Agg, but True gives<br>
nicer color boundaries. If antialiased is True and linewidths<br>
is too small, then there may be light-colored lines at the<br>
color boundaries caused by the antialiasing.<br>
* nchunk = 0 (default) for no subdivision of the domain;<br>
specify a positive integer to divide the domain into<br>
subdomains of roughly nchunk by nchunk points. This may<br>
never actually be advantageous, so this option may be<br>
removed. Chunking introduces artifacts at the chunk<br>
boundaries unless antialiased = False, or linewidths is<br>
set to a large enough value for the particular renderer and<br>
resolution.</tt></dd></dl>
<dl><dt><a name="Axes-contourf"><strong>contourf</strong></a>(self, *args, **kwargs)</dt><dd><tt>contour and contourf draw contour lines and filled contours,<br>
respectively. Except as noted, function signatures and return<br>
values are the same for both versions.<br>
<br>
contourf differs from the Matlab (TM) version in that it does not<br>
draw the polygon edges, because the contouring engine yields<br>
simply connected regions with branch cuts. To draw the edges,<br>
add line contours with calls to contour.<br>
<br>
<br>
Function signatures<br>
<br>
<a href="#Axes-contour">contour</a>(Z) - make a contour plot of an array Z. The level<br>
values are chosen automatically.<br>
<br>
<a href="#Axes-contour">contour</a>(X,Y,Z) - X,Y specify the (x,y) coordinates of the surface<br>
<br>
<a href="#Axes-contour">contour</a>(Z,N) and <a href="#Axes-contour">contour</a>(X,Y,Z,N) - contour N automatically-chosen<br>
levels.<br>
<br>
<a href="#Axes-contour">contour</a>(Z,V) and <a href="#Axes-contour">contour</a>(X,Y,Z,V) - draw len(V) contour lines,<br>
at the values specified in sequence V<br>
<br>
<a href="#Axes-contourf">contourf</a>(..., V) - fill the (len(V)-1) regions between the<br>
values in V<br>
<br>
<a href="#Axes-contour">contour</a>(Z, **kwargs) - Use keyword args to control colors, linewidth,<br>
origin, cmap ... see below<br>
<br>
X, Y, and Z must be arrays with the same dimensions.<br>
Z may be a masked array, but filled contouring may not handle<br>
internal masked regions correctly.<br>
<br>
C = <a href="#Axes-contour">contour</a>(...) returns a ContourSet object.<br>
<br>
<br>
Optional keyword args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* colors = None; or one of the following:<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different levels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all levels<br>
will be plotted in this color<br>
<br>
- if colors == None, the colormap specified by cmap will be used<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
* cmap = None: a cm Colormap instance from matplotlib.cm.<br>
- if cmap == None and colors == None, a default Colormap is used.<br>
<br>
* norm = None: a matplotlib.colors.Normalize instance for<br>
scaling data values to colors.<br>
- if norm == None, and colors == None, the default<br>
linear scaling is used.<br>
<br>
* origin = None: 'upper'|'lower'|'image'|None.<br>
If 'image', the rc value for image.origin will be used.<br>
If None (default), the first value of Z will correspond<br>
to the lower left corner, location (0,0).<br>
This keyword is active only if contourf is called with<br>
one or two arguments, that is, without explicitly<br>
specifying X and Y.<br>
<br>
* extent = None: (x0,x1,y0,y1); also active only if X and Y<br>
are not specified. If origin is not None, then extent is<br>
interpreted as in imshow: it gives the outer pixel boundaries.<br>
In this case, the position of Z[0,0] is the center of the<br>
pixel, not a corner.<br>
If origin is None, then (x0,y0) is the position of Z[0,0],<br>
and (x1,y1) is the position of Z[-1,-1].<br>
<br>
* locator = None: an instance of a ticker.Locator subclass;<br>
default is MaxNLocator. It is used to determine the<br>
contour levels if they are not given explicitly via the<br>
V argument.<br>
<br>
***** New: *****<br>
* extend = 'neither', 'both', 'min', 'max'<br>
Unless this is 'neither' (default), contour levels are<br>
automatically added to one or both ends of the range so that<br>
all data are included. These added ranges are then<br>
mapped to the special colormap values which default to<br>
the ends of the colormap range, but can be set via<br>
Colormap.set_under() and Colormap.set_over() methods.<br>
To replace clip_ends=True and V = [-100, 2, 1, 0, 1, 2, 100],<br>
use extend='both' and V = [2, 1, 0, 1, 2].<br>
****************<br>
<br>
contour only:<br>
* linewidths = None: or one of these:<br>
- a number - all levels will be plotted with this linewidth,<br>
e.g. linewidths = 0.6<br>
<br>
- a tuple of numbers, e.g. linewidths = (0.4, 0.8, 1.2) different<br>
levels will be plotted with different linewidths in the order<br>
specified<br>
<br>
- if linewidths == None, the default width in lines.linewidth in<br>
matplotlibrc is used<br>
<br>
contourf only:<br>
***** Obsolete: ****<br>
* clip_ends = True<br>
If False, the limits for color scaling are set to the<br>
minimum and maximum contour levels.<br>
True (default) clips the scaling limits. Example:<br>
if the contour boundaries are V = [-100, 2, 1, 0, 1, 2, 100],<br>
then the scaling limits will be [-100, 100] if clip_ends<br>
is False, and [-3, 3] if clip_ends is True.<br>
* linewidths = None or a number; default of 0.05 works for<br>
Postscript; a value of about 0.5 seems better for Agg.<br>
* antialiased = True (default) or False; if False, there is<br>
no need to increase the linewidths for Agg, but True gives<br>
nicer color boundaries. If antialiased is True and linewidths<br>
is too small, then there may be light-colored lines at the<br>
color boundaries caused by the antialiasing.<br>
* nchunk = 0 (default) for no subdivision of the domain;<br>
specify a positive integer to divide the domain into<br>
subdomains of roughly nchunk by nchunk points. This may<br>
never actually be advantageous, so this option may be<br>
removed. Chunking introduces artifacts at the chunk<br>
boundaries unless antialiased = False, or linewidths is<br>
set to a large enough value for the particular renderer and<br>
resolution.</tt></dd></dl>
<dl><dt><a name="Axes-csd"><strong>csd</strong></a>(self, x, y, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, window<font color="#909090">=<function window_hanning at 0xb5bc7764></font>, noverlap<font color="#909090">=0</font>, **kwargs)</dt><dd><tt>CSD(x, y, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0, **kwargs)<br>
The cross spectral density Pxy by Welches average periodogram method.<br>
The vectors x and y are divided into NFFT length segments. Each<br>
segment is detrended by function detrend and windowed by function<br>
window. The product of the direct FFTs of x and y are averaged over<br>
each segment to compute Pxy, with a scaling to correct for power loss<br>
due to windowing.<br>
See the PSD help for a description of the optional parameters.<br>
Returns the tuple Pxy, freqs. Pxy is the cross spectrum (complex<br>
valued), and 10*log10(|Pxy|) is plotted<br>
Refs:<br>
Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)<br>
kwargs control the Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-disconnect"><strong>disconnect</strong></a>(self, cid)</dt><dd><tt>disconnect from the <a href="#Axes">Axes</a> event.</tt></dd></dl>
<dl><dt><a name="Axes-draw"><strong>draw</strong></a>(self, renderer<font color="#909090">=None</font>, inframe<font color="#909090">=False</font>)</dt><dd><tt>Draw everything (plot lines, axes, labels)</tt></dd></dl>
<dl><dt><a name="Axes-draw_artist"><strong>draw_artist</strong></a>(self, a)</dt><dd><tt>This method can only be used after an initial draw which<br>
caches the renderer. It is used to efficiently update <a href="#Axes">Axes</a><br>
data (axis ticks, labels, etc are not updated)</tt></dd></dl>
<dl><dt><a name="Axes-errorbar"><strong>errorbar</strong></a>(self, x, y, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, fmt<font color="#909090">='b-'</font>, ecolor<font color="#909090">=None</font>, capsize<font color="#909090">=3</font>, barsabove<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>ERRORBAR(x, y, yerr=None, xerr=None,<br>
fmt='b-', ecolor=None, capsize=3, barsabove=False)<br>
Plot x versus y with error deltas in yerr and xerr.<br>
Vertical errorbars are plotted if yerr is not None<br>
Horizontal errorbars are plotted if xerr is not None<br>
xerr and yerr may be any of:<br>
a rank-0, Nx1 Numpy array - symmetric errorbars +/- value<br>
an N-element list or tuple - symmetric errorbars +/- value<br>
a rank-1, Nx2 Numpy array - asymmetric errorbars -column1/+column2<br>
Alternatively, x, y, xerr, and yerr can all be scalars, which<br>
plots a single error bar at x, y.<br>
fmt is the plot format symbol for y. if fmt is None, just<br>
plot the errorbars with no line symbols. This can be useful<br>
for creating a bar plot with errorbars<br>
ecolor is a matplotlib color arg which gives the color the<br>
errorbar lines; if None, use the marker color.<br>
capsize is the size of the error bar caps in points<br>
barsabove, if True, will plot the errorbars above the plot symbols<br>
- default is below<br>
kwargs are passed on to the plot command for the markers.<br>
So you can add additional key=value pairs to control the<br>
errorbar markers. For example, this code makes big red<br>
squares with thick green edges<br>
>>> x,y,yerr = rand(3,10)<br>
>>> <a href="#Axes-errorbar">errorbar</a>(x, y, yerr, marker='s',<br>
mfc='red', mec='green', ms=20, mew=4)<br>
mfc, mec, ms and mew are aliases for the longer property<br>
names, markerfacecolor, markeredgecolor, markersize and<br>
markeredgewith.<br>
valid kwargs for the marker properties are<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number<br>
Return value is a length 3 tuple. The first element is the<br>
Line2D instance for the y symbol lines. The second element is<br>
a list of error bar cap lines, the third element is a list of<br>
line collections for the horizontal and vertical error ranges</tt></dd></dl>
<dl><dt><a name="Axes-fill"><strong>fill</strong></a>(self, *args, **kwargs)</dt><dd><tt>FILL(*args, **kwargs)<br>
plot filled polygons. *args is a variable length argument, allowing<br>
for multiple x,y pairs with an optional color format string; see plot<br>
for details on the argument parsing. For example, all of the<br>
following are legal, assuming ax is an <a href="#Axes">Axes</a> instance:<br>
ax.<a href="#Axes-fill">fill</a>(x,y) # plot polygon with vertices at x,y<br>
ax.<a href="#Axes-fill">fill</a>(x,y, 'b' ) # plot polygon with vertices at x,y in blue<br>
An arbitrary number of x, y, color groups can be specified, as in<br>
ax.<a href="#Axes-fill">fill</a>(x1, y1, 'g', x2, y2, 'r')<br>
Return value is a list of patches that were added<br>
The same color strings that plot supports are supported by the fill<br>
format string.<br>
kwargs control the Polygon properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-format_coord"><strong>format_coord</strong></a>(self, x, y)</dt><dd><tt>return a format string formatting the x, y coord</tt></dd></dl>
<dl><dt><a name="Axes-format_xdata"><strong>format_xdata</strong></a>(self, x)</dt><dd><tt>Return x string formatted. This function will use the attribute<br>
self.<strong>fmt_xdata</strong> if it is callable, else will fall back on the xaxis<br>
major formatter</tt></dd></dl>
<dl><dt><a name="Axes-format_ydata"><strong>format_ydata</strong></a>(self, y)</dt><dd><tt>Return y string formatted. This function will use the attribute<br>
self.<strong>fmt_ydata</strong> if it is callable, else will fall back on the yaxis<br>
major formatter</tt></dd></dl>
<dl><dt><a name="Axes-get_adjustable"><strong>get_adjustable</strong></a>(self)</dt></dl>
<dl><dt><a name="Axes-get_anchor"><strong>get_anchor</strong></a>(self)</dt></dl>
<dl><dt><a name="Axes-get_aspect"><strong>get_aspect</strong></a>(self)</dt></dl>
<dl><dt><a name="Axes-get_autoscale_on"><strong>get_autoscale_on</strong></a>(self)</dt><dd><tt>Get whether autoscaling is applied on plot commands</tt></dd></dl>
<dl><dt><a name="Axes-get_axis_bgcolor"><strong>get_axis_bgcolor</strong></a>(self)</dt><dd><tt>Return the axis background color</tt></dd></dl>
<dl><dt><a name="Axes-get_axisbelow"><strong>get_axisbelow</strong></a>(self)</dt><dd><tt>Get whether axist below is true or not</tt></dd></dl>
<dl><dt><a name="Axes-get_child_artists"><strong>get_child_artists</strong></a>(self)</dt><dd><tt>Return a list of artists the axes contains. Deprecated</tt></dd></dl>
<dl><dt><a name="Axes-get_children"><strong>get_children</strong></a>(self)</dt><dd><tt>return a list of child artists</tt></dd></dl>
<dl><dt><a name="Axes-get_cursor_props"><strong>get_cursor_props</strong></a>(self)</dt><dd><tt>return the cursor props as a linewidth, color tuple where<br>
linewidth is a float and color is an RGBA tuple</tt></dd></dl>
<dl><dt><a name="Axes-get_frame"><strong>get_frame</strong></a>(self)</dt><dd><tt>Return the axes Rectangle frame</tt></dd></dl>
<dl><dt><a name="Axes-get_frame_on"><strong>get_frame_on</strong></a>(self)</dt><dd><tt>Get whether the axes rectangle patch is drawn</tt></dd></dl>
<dl><dt><a name="Axes-get_images"><strong>get_images</strong></a>(self)</dt><dd><tt>return a list of <a href="#Axes">Axes</a> images contained by the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="Axes-get_legend"><strong>get_legend</strong></a>(self)</dt><dd><tt>Return the Legend instance, or None if no legend is defined</tt></dd></dl>
<dl><dt><a name="Axes-get_lines"><strong>get_lines</strong></a>(self)</dt><dd><tt>Return a list of lines contained by the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="Axes-get_navigate"><strong>get_navigate</strong></a>(self)</dt><dd><tt>Get whether the axes responds to navigation commands</tt></dd></dl>
<dl><dt><a name="Axes-get_navigate_mode"><strong>get_navigate_mode</strong></a>(self)</dt><dd><tt>Get the navigation toolbar button status: 'PAN', 'ZOOM', or None</tt></dd></dl>
<dl><dt><a name="Axes-get_position"><strong>get_position</strong></a>(self, original<font color="#909090">=False</font>)</dt><dd><tt>Return the axes rectangle left, bottom, width, height</tt></dd></dl>
<dl><dt><a name="Axes-get_renderer_cache"><strong>get_renderer_cache</strong></a>(self)</dt></dl>
<dl><dt><a name="Axes-get_window_extent"><strong>get_window_extent</strong></a>(self, *args, **kwargs)</dt><dd><tt>get the axes bounding box in display space; args and kwargs are empty</tt></dd></dl>
<dl><dt><a name="Axes-get_xaxis"><strong>get_xaxis</strong></a>(self)</dt><dd><tt>Return the XAxis instance</tt></dd></dl>
<dl><dt><a name="Axes-get_xgridlines"><strong>get_xgridlines</strong></a>(self)</dt><dd><tt>Get the x grid lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="Axes-get_xlim"><strong>get_xlim</strong></a>(self)</dt><dd><tt>Get the x axis range [xmin, xmax]</tt></dd></dl>
<dl><dt><a name="Axes-get_xscale"><strong>get_xscale</strong></a>(self)</dt><dd><tt>return the xaxis scale string: log or linear</tt></dd></dl>
<dl><dt><a name="Axes-get_xticklabels"><strong>get_xticklabels</strong></a>(self)</dt><dd><tt>Get the xtick labels as a list of Text instances</tt></dd></dl>
<dl><dt><a name="Axes-get_xticklines"><strong>get_xticklines</strong></a>(self)</dt><dd><tt>Get the xtick lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="Axes-get_xticks"><strong>get_xticks</strong></a>(self)</dt><dd><tt>Return the x ticks as a list of locations</tt></dd></dl>
<dl><dt><a name="Axes-get_yaxis"><strong>get_yaxis</strong></a>(self)</dt><dd><tt>Return the YAxis instance</tt></dd></dl>
<dl><dt><a name="Axes-get_ygridlines"><strong>get_ygridlines</strong></a>(self)</dt><dd><tt>Get the y grid lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="Axes-get_ylim"><strong>get_ylim</strong></a>(self)</dt><dd><tt>Get the y axis range [ymin, ymax]</tt></dd></dl>
<dl><dt><a name="Axes-get_yscale"><strong>get_yscale</strong></a>(self)</dt><dd><tt>return the yaxis scale string: log or linear</tt></dd></dl>
<dl><dt><a name="Axes-get_yticklabels"><strong>get_yticklabels</strong></a>(self)</dt><dd><tt>Get the ytick labels as a list of Text instances</tt></dd></dl>
<dl><dt><a name="Axes-get_yticklines"><strong>get_yticklines</strong></a>(self)</dt><dd><tt>Get the ytick lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="Axes-get_yticks"><strong>get_yticks</strong></a>(self)</dt><dd><tt>Return the y ticks as a list of locations</tt></dd></dl>
<dl><dt><a name="Axes-grid"><strong>grid</strong></a>(self, b<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>GRID(self, b=None, **kwargs)<br>
Set the axes grids on or off; b is a boolean<br>
if b is None and len(kwargs)==0, toggle the grid state. if<br>
kwargs are supplied, it is assumed that you want a grid and b<br>
is thus set to True<br>
kawrgs are used to set the grid line properties, eg<br>
ax.<a href="#Axes-grid">grid</a>(color='r', linestyle='-', linewidth=2)<br>
Valid Line2D kwargs are<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-has_data"><strong>has_data</strong></a>(self)</dt><dd><tt>Return true if any artists have been added to axes.<br>
<br>
This should not be used to determine whether the dataLim<br>
need to be updated, and may not actually be useful for<br>
anything.</tt></dd></dl>
<dl><dt><a name="Axes-hist"><strong>hist</strong></a>(self, x, bins<font color="#909090">=10</font>, normed<font color="#909090">=0</font>, bottom<font color="#909090">=None</font>, align<font color="#909090">='edge'</font>, orientation<font color="#909090">='vertical'</font>, width<font color="#909090">=None</font>, log<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>HIST(x, bins=10, normed=0, bottom=None,<br>
align='edge', orientation='vertical', width=None,<br>
log=False, **kwargs)<br>
Compute the histogram of x. bins is either an integer number of<br>
bins or a sequence giving the bins. x are the data to be binned.<br>
The return values is (n, bins, patches)<br>
If normed is true, the first element of the return tuple will<br>
be the counts normalized to form a probability density, ie,<br>
n/(len(x)*dbin). In a probability density, the integral of<br>
the histogram should be one (we assume equally spaced bins);<br>
you can verify that with<br>
# trapezoidal integration of the probability density function<br>
from matplotlib.mlab import trapz<br>
pdf, bins, patches = ax.<a href="#Axes-hist">hist</a>(...)<br>
print trapz(bins, pdf)<br>
align = 'edge' | 'center'. Interprets bins either as edge<br>
or center values<br>
orientation = 'horizontal' | 'vertical'. If horizontal, barh<br>
will be used and the "bottom" kwarg will be the left edges.<br>
width: the width of the bars. If None, automatically compute<br>
the width.<br>
log: if True, the histogram axis will be set to a log scale<br>
kwargs are used to update the properties of the<br>
hist Rectangles:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-hlines"><strong>hlines</strong></a>(self, y, xmin, xmax, colors<font color="#909090">='k'</font>, linestyle<font color="#909090">='solid'</font>, label<font color="#909090">=''</font>, **kwargs)</dt><dd><tt>HLINES(y, xmin, xmax, colors='k', linestyle='solid', **kwargs)<br>
plot horizontal lines at each y from xmin to xmax. xmin or xmax can<br>
be scalars or len(x) numpy arrays. If they are scalars, then the<br>
respective values are constant, else the widths of the lines are<br>
determined by xmin and xmax<br>
colors is a line collections color args, either a single color or a len(x) list of colors<br>
linestyle is one of solid|dashed|dashdot|dotted<br>
Returns the LineCollection that was added</tt></dd></dl>
<dl><dt><a name="Axes-hold"><strong>hold</strong></a>(self, b<font color="#909090">=None</font>)</dt><dd><tt>HOLD(b=None)<br>
<br>
Set the hold state. If hold is None (default), toggle the<br>
hold state. Else set the hold state to boolean value b.<br>
<br>
Eg<br>
<a href="#Axes-hold">hold</a>() # toggle hold<br>
<a href="#Axes-hold">hold</a>(True) # hold is on<br>
<a href="#Axes-hold">hold</a>(False) # hold is off<br>
<br>
<br>
When hold is True, subsequent plot commands will be added to<br>
the current axes. When hold is False, the current axes and<br>
figure will be cleared on the next plot command</tt></dd></dl>
<dl><dt><a name="Axes-imshow"><strong>imshow</strong></a>(self, X, cmap<font color="#909090">=None</font>, norm<font color="#909090">=None</font>, aspect<font color="#909090">=None</font>, interpolation<font color="#909090">=None</font>, alpha<font color="#909090">=1.0</font>, vmin<font color="#909090">=None</font>, vmax<font color="#909090">=None</font>, origin<font color="#909090">=None</font>, extent<font color="#909090">=None</font>, shape<font color="#909090">=None</font>, filternorm<font color="#909090">=1</font>, filterrad<font color="#909090">=4.0</font>, imlim<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>IMSHOW(X, cmap=None, norm=None, aspect=None, interpolation=None,<br>
alpha=1.0, vmin=None, vmax=None, origin=None, extent=None)<br>
<br>
IMSHOW(X) - plot image X to current axes, resampling to scale to axes<br>
size (X may be numarray/Numeric array or PIL image)<br>
<br>
IMSHOW(X, **kwargs) - Use keyword args to control image scaling,<br>
colormapping etc. See below for details<br>
<br>
<br>
Display the image in X to current axes. X may be a float array, a<br>
UInt8 array or a PIL image. If X is an array, X can have the following<br>
shapes:<br>
<br>
MxN : luminance (grayscale, float array only)<br>
<br>
MxNx3 : RGB (float or UInt8 array)<br>
<br>
MxNx4 : RGBA (float or UInt8 array)<br>
<br>
The value for each component of MxNx3 and MxNx4 float arrays should be<br>
in the range 0.0 to 1.0; MxN float arrays may be normalised.<br>
<br>
A matplotlib.image.AxesImage instance is returned<br>
<br>
The following kwargs are allowed:<br>
<br>
* cmap is a cm colormap instance, eg cm.jet. If None, default to rc<br>
image.cmap value (Ignored when X has RGB(A) information)<br>
<br>
* aspect is one of: auto, equal, or a number. If None, default to rc<br>
image.aspect value<br>
<br>
* interpolation is one of:<br>
<br>
'nearest', 'bilinear', 'bicubic', 'spline16', 'spline36',<br>
'hanning', 'hamming', 'hermite', 'kaiser', 'quadric',<br>
'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc',<br>
'lanczos', 'blackman'<br>
<br>
if interpolation is None, default to rc<br>
image.interpolation. See also th the filternorm and<br>
filterrad parameters<br>
<br>
* norm is a matplotlib.colors.Normalize instance; default is<br>
normalization(). This scales luminance -> 0-1 (only used for an<br>
MxN float array).<br>
<br>
* vmin and vmax are used to scale a luminance image to 0-1. If<br>
either is None, the min and max of the luminance values will be<br>
used. Note if you pass a norm instance, the settings for vmin and<br>
vmax will be ignored.<br>
<br>
* alpha = 1.0 : the alpha blending value<br>
<br>
* origin is 'upper' or 'lower', to place the [0,0]<br>
index of the array in the upper left or lower left corner of<br>
the axes. If None, default to rc image.origin<br>
<br>
* extent is (left, right, bottom, top) data values of the<br>
axes. The default assigns zero-based row, column indices<br>
to the x, y centers of the pixels.<br>
<br>
* shape is for raw buffer images<br>
<br>
* filternorm is a parameter for the antigrain image resize<br>
filter. From the antigrain documentation, if normalize=1,<br>
the filter normalizes integer values and corrects the<br>
rounding errors. It doesn't do anything with the source<br>
floating point values, it corrects only integers according<br>
to the rule of 1.0 which means that any sum of pixel<br>
weights must be equal to 1.0. So, the filter function<br>
must produce a graph of the proper shape.<br>
<br>
* filterrad: the filter radius for filters that have a radius<br>
parameter, ie when interpolation is one of: 'sinc',<br>
'lanczos' or 'blackman'<br>
<br>
Additional kwargs are matplotlib.artist properties</tt></dd></dl>
<dl><dt><a name="Axes-in_axes"><strong>in_axes</strong></a>(self, xwin, ywin)</dt><dd><tt>return True is the point xwin, ywin (display coords) are in the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="Axes-ishold"><strong>ishold</strong></a>(self)</dt><dd><tt>return the HOLD status of the axes</tt></dd></dl>
<dl><dt><a name="Axes-legend"><strong>legend</strong></a>(self, *args, **kwargs)</dt><dd><tt>LEGEND(*args, **kwargs)<br>
<br>
Place a legend on the current axes at location loc. Labels are a<br>
sequence of strings and loc can be a string or an integer specifying<br>
the legend location<br>
<br>
USAGE:<br>
<br>
Make a legend with existing lines<br>
<br>
>>> <a href="#Axes-legend">legend</a>()<br>
<br>
legend by itself will try and build a legend using the label<br>
property of the lines/patches/collections. You can set the label of<br>
a line by doing <a href="#Axes-plot">plot</a>(x, y, label='my data') or line.<a href="#Axes-set_label">set_label</a>('my<br>
data'). If label is set to '_nolegend_', the item will not be shown<br>
in legend.<br>
<br>
# automatically generate the legend from labels<br>
<a href="#Axes-legend">legend</a>( ('label1', 'label2', 'label3') )<br>
<br>
# Make a legend for a list of lines and labels<br>
<a href="#Axes-legend">legend</a>( (line1, line2, line3), ('label1', 'label2', 'label3') )<br>
<br>
# Make a legend at a given location, using a location argument<br>
# <a href="#Axes-legend">legend</a>( LABELS, LOC ) or<br>
# <a href="#Axes-legend">legend</a>( LINES, LABELS, LOC )<br>
<a href="#Axes-legend">legend</a>( ('label1', 'label2', 'label3'), loc='upper left')<br>
<a href="#Axes-legend">legend</a>( (line1, line2, line3), ('label1', 'label2', 'label3'), loc=2)<br>
<br>
The location codes are<br>
<br>
'best' : 0,<br>
'upper right' : 1, (default)<br>
'upper left' : 2,<br>
'lower left' : 3,<br>
'lower right' : 4,<br>
'right' : 5,<br>
'center left' : 6,<br>
'center right' : 7,<br>
'lower center' : 8,<br>
'upper center' : 9,<br>
'center' : 10,<br>
<br>
If none of these are suitable, loc can be a 2-tuple giving x,y<br>
in axes coords, ie,<br>
<br>
loc = 0, 1 is left top<br>
loc = 0.5, 0.5 is center, center<br>
<br>
and so on. The following kwargs are supported:<br>
<br>
isaxes=True # whether this is an axes legend<br>
numpoints = 4 # the number of points in the legend line<br>
prop = FontProperties(size='smaller') # the font property<br>
pad = 0.2 # the fractional whitespace inside the legend border<br>
markerscale = 0.6 # the relative size of legend markers vs. original<br>
shadow # if True, draw a shadow behind legend<br>
labelsep = 0.005 # the vertical space between the legend entries<br>
handlelen = 0.05 # the length of the legend lines<br>
handletextsep = 0.02 # the space between the legend line and legend text<br>
axespad = 0.02 # the border between the axes and legend edge</tt></dd></dl>
<dl><dt><a name="Axes-loglog"><strong>loglog</strong></a>(self, *args, **kwargs)</dt><dd><tt>LOGLOG(*args, **kwargs)<br>
Make a loglog plot with log scaling on the a and y axis. The args<br>
to semilog x are the same as the args to plot. See help plot for<br>
more info.<br>
Optional keyword args supported are any of the kwargs<br>
supported by plot or set_xscale or set_yscale. Notable, for<br>
log scaling:<br>
* basex: base of the x logarithm<br>
* subsx: the location of the minor ticks; None defaults to<br>
autosubs, which depend on the number of decades in the<br>
plot; see set_xscale for details<br>
* basey: base of the y logarithm<br>
* subsy: the location of the minor yticks; None defaults to<br>
autosubs, which depend on the number of decades in the<br>
plot; see set_yscale for details<br>
The remaining valid kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-matshow"><strong>matshow</strong></a>(self, Z, **kwargs)</dt><dd><tt>Plot a matrix as an image.<br>
<br>
The matrix will be shown the way it would be printed,<br>
with the first row at the top. Row and column numbering<br>
is zero-based.<br>
<br>
Argument:<br>
Z anything that can be interpreted as a 2-D array<br>
<br>
kwargs: all are passed to imshow. matshow sets defaults<br>
for extent, origin, interpolation, and aspect; use care<br>
in overriding the extent and origin kwargs, because they<br>
interact. (Also, if you want to change them, you probably<br>
should be using imshow directly in your own version of<br>
matshow.)<br>
<br>
Returns: an AxesImage instance</tt></dd></dl>
<dl><dt><a name="Axes-panx"><strong>panx</strong></a>(self, numsteps)</dt><dd><tt>Pan the x axis numsteps (plus pan right, minus pan left)</tt></dd></dl>
<dl><dt><a name="Axes-pany"><strong>pany</strong></a>(self, numsteps)</dt><dd><tt>Pan the x axis numsteps (plus pan up, minus pan down)</tt></dd></dl>
<dl><dt><a name="Axes-pcolor"><strong>pcolor</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#Axes-pcolor">pcolor</a>(*args, **kwargs): pseudocolor plot of a 2-D array<br>
Function signatures<br>
<a href="#Axes-pcolor">pcolor</a>(C, **kwargs)<br>
<a href="#Axes-pcolor">pcolor</a>(X, Y, C, **kwargs)<br>
C is the array of color values<br>
X and Y, if given, specify the (x,y) coordinates of the colored<br>
quadrilaterals; the quadrilateral for C[i,j] has corners at<br>
(X[i,j],Y[i,j]), (X[i,j+1],Y[i,j+1]), (X[i+1,j],Y[i+1,j]),<br>
(X[i+1,j+1],Y[i+1,j+1]). Ideally the dimensions of X and Y<br>
should be one greater than those of C; if the dimensions are the<br>
same, then the last row and column of C will be ignored.<br>
Note that the the column index corresponds to the x-coordinate,<br>
and the row index corresponds to y; for details, see<br>
the "Grid Orientation" section below.<br>
If either or both of X and Y are 1-D arrays or column vectors,<br>
they will be expanded as needed into the appropriate 2-D arrays,<br>
making a rectangular grid.<br>
X,Y and C may be masked arrays. If either C[i,j], or one<br>
of the vertices surrounding C[i,j] (X or Y at [i,j],[i+1,j],<br>
[i,j+1],[i=1,j+1]) is masked, nothing is plotted.<br>
Optional keyword args are shown with their defaults below (you must<br>
use kwargs for these):<br>
* cmap = cm.jet : a cm Colormap instance from matplotlib.cm.<br>
defaults to cm.jet<br>
* norm = Normalize() : matplotlib.colors.Normalize instance<br>
is used to scale luminance data to 0,1.<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used. If you pass a norm<br>
instance, vmin and vmax will be None<br>
* shading = 'flat' : or 'faceted'. If 'faceted', a black grid is<br>
drawn around each rectangle; if 'flat', edges are not drawn<br>
* alpha=1.0 : the alpha blending value<br>
Return value is a matplotlib.collections.PatchCollection<br>
object<br>
Grid Orientation<br>
The orientation follows the Matlab(TM) convention: an<br>
array C with shape (nrows, ncolumns) is plotted with<br>
the column number as X and the row number as Y, increasing<br>
up; hence it is plotted the way the array would be printed,<br>
except that the Y axis is reversed. That is, C is taken<br>
as C(y,x).<br>
Similarly for meshgrid:<br>
x = arange(5)<br>
y = arange(3)<br>
X, Y = meshgrid(x,y)<br>
is equivalent to<br>
X = array([[0, 1, 2, 3, 4],<br>
[0, 1, 2, 3, 4],<br>
[0, 1, 2, 3, 4]])<br>
Y = array([[0, 0, 0, 0, 0],<br>
[1, 1, 1, 1, 1],<br>
[2, 2, 2, 2, 2]])<br>
so if you have<br>
C = rand( len(x), len(y))<br>
then you need<br>
<a href="#Axes-pcolor">pcolor</a>(X, Y, transpose(C))<br>
or<br>
<a href="#Axes-pcolor">pcolor</a>(transpose(C))<br>
Dimensions<br>
Matlab pcolor always discards<br>
the last row and column of C, but matplotlib displays<br>
the last row and column if X and Y are not specified, or<br>
if X and Y have one more row and column than C.<br>
kwargs can be used to control the PolyCollection properties:<br>
alpha: float<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
edgecolor: matplotlib color arg or sequence of rgba tuples<br>
facecolor: matplotlib color arg or sequence of rgba tuples<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-pcolor_classic"><strong>pcolor_classic</strong></a>(self, *args)</dt><dd><tt>pcolor_classic is no longer available; please use pcolor,<br>
which is a drop-in replacement.</tt></dd></dl>
<dl><dt><a name="Axes-pcolormesh"><strong>pcolormesh</strong></a>(self, *args, **kwargs)</dt><dd><tt>PCOLORMESH(*args, **kwargs)<br>
Function signatures<br>
PCOLORMESH(C) - make a pseudocolor plot of matrix C<br>
PCOLORMESH(X, Y, C) - a pseudo color plot of C on the matrices X and Y<br>
PCOLORMESH(C, **kwargs) - Use keyword args to control colormapping and<br>
scaling; see below<br>
C may be a masked array, but X and Y may not. Masked array support<br>
is implemented via cmap and norm; in contrast, pcolor simply does<br>
not draw quadrilaterals with masked colors or vertices.<br>
Optional keyword args are shown with their defaults below (you must<br>
use kwargs for these):<br>
* cmap = cm.jet : a cm Colormap instance from matplotlib.cm.<br>
defaults to cm.jet<br>
* norm = Normalize() : matplotlib.colors.Normalize instance<br>
is used to scale luminance data to 0,1. Instantiate it<br>
with clip=False if C is a masked array.<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used.<br>
* shading = 'flat' : or 'faceted'. If 'faceted', a black grid is<br>
drawn around each rectangle; if 'flat', edge colors are same as<br>
face colors<br>
* alpha=1.0 : the alpha blending value<br>
Return value is a matplotlib.collections.PatchCollection<br>
object<br>
See pcolor for an explantion of the grid orientation and the<br>
expansion of 1-D X and/or Y to 2-D arrays.<br>
kwargs can be used to control the QuadMesh polygon collection properties:<br>
alpha: float<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
edgecolor: matplotlib color arg or sequence of rgba tuples<br>
facecolor: matplotlib color arg or sequence of rgba tuples<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-pick"><strong>pick</strong></a>(self, *args)</dt><dd><tt><a href="#Axes-pick">pick</a>(mouseevent)<br>
<br>
each child artist will fire a pick event if mouseevent is over<br>
the artist and the artist has picker set</tt></dd></dl>
<dl><dt><a name="Axes-pie"><strong>pie</strong></a>(self, x, explode<font color="#909090">=None</font>, labels<font color="#909090">=None</font>, colors<font color="#909090">=None</font>, autopct<font color="#909090">=None</font>, pctdistance<font color="#909090">=0.59999999999999998</font>, shadow<font color="#909090">=False</font>)</dt><dd><tt>PIE(x, explode=None, labels=None,<br>
colors=('b', 'g', 'r', 'c', 'm', 'y', 'k', 'w'),<br>
autopct=None, pctdistance=0.6, shadow=False)<br>
<br>
Make a pie chart of array x. The fractional area of each wedge is<br>
given by x/sum(x). If sum(x)<=1, then the values of x give the<br>
fractional area directly and the array will not be normalized.<br>
<br>
- explode, if not None, is a len(x) array which specifies the<br>
fraction of the radius to offset that wedge.<br>
<br>
- colors is a sequence of matplotlib color args that the pie chart<br>
will cycle.<br>
<br>
- labels, if not None, is a len(x) list of labels.<br>
<br>
- autopct, if not None, is a string or function used to label the<br>
wedges with their numeric value. The label will be placed inside<br>
the wedge. If it is a format string, the label will be fmt%pct.<br>
If it is a function, it will be called<br>
<br>
- pctdistance is the ratio between the center of each pie slice<br>
and the start of the text generated by autopct. Ignored if autopct<br>
is None; default is 0.6.<br>
<br>
- shadow, if True, will draw a shadow beneath the pie.<br>
<br>
The pie chart will probably look best if the figure and axes are<br>
square. Eg,<br>
<br>
figure(figsize=(8,8))<br>
ax = axes([0.1, 0.1, 0.8, 0.8])<br>
<br>
Return value:<br>
<br>
If autopct is None, return a list of (patches, texts), where patches<br>
is a sequence of matplotlib.patches.Wedge instances and texts is a<br>
list of the label Text instnaces<br>
<br>
If autopct is not None, return (patches, texts, autotexts), where<br>
patches and texts are as above, and autotexts is a list of text<br>
instances for the numeric labels</tt></dd></dl>
<dl><dt><a name="Axes-plot"><strong>plot</strong></a>(self, *args, **kwargs)</dt><dd><tt>PLOT(*args, **kwargs)<br>
Plot lines and/or markers to the <a href="#Axes">Axes</a>. *args is a variable length<br>
argument, allowing for multiple x,y pairs with an optional format<br>
string. For example, each of the following is legal<br>
<a href="#Axes-plot">plot</a>(x,y) # plot x and y using the default line style and color<br>
<a href="#Axes-plot">plot</a>(x,y, 'bo') # plot x and y using blue circle markers<br>
<a href="#Axes-plot">plot</a>(y) # plot y using x as index array 0..N-1<br>
<a href="#Axes-plot">plot</a>(y, 'r+') # ditto, but with red plusses<br>
If x and/or y is 2-Dimensional, then the corresponding columns<br>
will be plotted.<br>
An arbitrary number of x, y, fmt groups can be specified, as in<br>
a.<a href="#Axes-plot">plot</a>(x1, y1, 'g^', x2, y2, 'g-')<br>
Return value is a list of lines that were added.<br>
The following line styles are supported:<br>
- : solid line<br>
-- : dashed line<br>
-. : dash-dot line<br>
: : dotted line<br>
. : points<br>
, : pixels<br>
o : circle symbols<br>
^ : triangle up symbols<br>
v : triangle down symbols<br>
< : triangle left symbols<br>
> : triangle right symbols<br>
s : square symbols<br>
+ : plus symbols<br>
x : cross symbols<br>
D : diamond symbols<br>
d : thin diamond symbols<br>
1 : tripod down symbols<br>
2 : tripod up symbols<br>
3 : tripod left symbols<br>
4 : tripod right symbols<br>
h : hexagon symbols<br>
H : rotated hexagon symbols<br>
p : pentagon symbols<br>
| : vertical line symbols<br>
_ : horizontal line symbols<br>
steps : use gnuplot style 'steps' # kwarg only<br>
The following color abbreviations are supported<br>
b : blue<br>
g : green<br>
r : red<br>
c : cyan<br>
m : magenta<br>
y : yellow<br>
k : black<br>
w : white<br>
In addition, you can specify colors in many weird and<br>
wonderful ways, including full names 'green', hex strings<br>
'#008000', RGB or RGBA tuples (0,1,0,1) or grayscale<br>
intensities as a string '0.8'.<br>
Line styles and colors are combined in a single format string, as in<br>
'bo' for blue circles.<br>
The **kwargs can be used to set line properties (any property that has<br>
a set_* method). You can use this to set a line label (for auto<br>
legends), linewidth, anitialising, marker face color, etc. Here is an<br>
example:<br>
<a href="#Axes-plot">plot</a>([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2)<br>
<a href="#Axes-plot">plot</a>([1,2,3], [1,4,9], 'rs', label='line 2')<br>
<a href="#Axes-axis">axis</a>([0, 4, 0, 10])<br>
<a href="#Axes-legend">legend</a>()<br>
If you make multiple lines with one plot command, the kwargs apply<br>
to all those lines, eg<br>
<a href="#Axes-plot">plot</a>(x1, y1, x2, y2, antialised=False)<br>
Neither line will be antialiased.<br>
The kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number<br>
kwargs scalex and scaley, if defined, are passed on<br>
to autoscale_view to determine whether the x and y axes are<br>
autoscaled; default True. See <a href="#Axes">Axes</a>.autoscale_view for more<br>
information</tt></dd></dl>
<dl><dt><a name="Axes-plot_date"><strong>plot_date</strong></a>(self, x, y, fmt<font color="#909090">='bo'</font>, tz<font color="#909090">=None</font>, xdate<font color="#909090">=True</font>, ydate<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>PLOT_DATE(x, y, fmt='bo', tz=None, xdate=True, ydate=False, **kwargs)<br>
Similar to the <a href="#Axes-plot">plot</a>() command, except the x or y (or both) data<br>
is considered to be dates, and the axis is labeled accordingly.<br>
x or y (or both) can be a sequence of dates represented as<br>
float days since 0001-01-01 UTC.<br>
fmt is a plot format string.<br>
tz is the time zone to use in labelling dates. Defaults to rc value.<br>
If xdate is True, the x-axis will be labeled with dates.<br>
If ydate is True, the y-axis will be labeled with dates.<br>
Note if you are using custom date tickers and formatters, it<br>
may be necessary to set the formatters/locators after the call<br>
to plot_date since plot_date will set the default tick locator<br>
to AutoDateLocator (if the tick locator is not already set to<br>
a DateLocator instance) and the default tick formatter to<br>
AutoDateFormatter (if the tick formatter is not already set to<br>
a DateFormatter instance).<br>
Valid kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number<br>
See matplotlib.dates for helper functions date2num, num2date<br>
and drange for help on creating the required floating point dates</tt></dd></dl>
<dl><dt><a name="Axes-psd"><strong>psd</strong></a>(self, x, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, window<font color="#909090">=<function window_hanning at 0xb5bc7764></font>, noverlap<font color="#909090">=0</font>, **kwargs)</dt><dd><tt>PSD(x, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0, **kwargs)<br>
The power spectral density by Welches average periodogram method. The<br>
vector x is divided into NFFT length segments. Each segment is<br>
detrended by function detrend and windowed by function window.<br>
noperlap gives the length of the overlap between segments. The<br>
absolute(fft(segment))**2 of each segment are averaged to compute Pxx,<br>
with a scaling to correct for power loss due to windowing. Fs is the<br>
sampling frequency.<br>
NFFT is the length of the fft segment; must be a power of 2<br>
Fs is the sampling frequency.<br>
detrend - the function applied to each segment before fft-ing,<br>
designed to remove the mean or linear trend. Unlike in matlab,<br>
where the detrend parameter is a vector, in matplotlib is it a<br>
function. The mlab module defines detrend_none, detrend_mean,<br>
detrend_linear, but you can use a custom function as well.<br>
window - the function used to window the segments. window is a<br>
function, unlike in matlab(TM) where it is a vector. mlab defines<br>
window_none, window_hanning, but you can use a custom function<br>
as well.<br>
noverlap gives the length of the overlap between segments.<br>
Returns the tuple Pxx, freqs<br>
For plotting, the power is plotted as 10*log10(pxx)) for decibels,<br>
though pxx itself is returned<br>
Refs:<br>
Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)<br>
kwargs control the Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-quiver"><strong>quiver</strong></a>(self, *args, **kw)</dt><dd><tt>Plot a 2-D field of arrows.<br>
<br>
Function signatures:<br>
<br>
<a href="#Axes-quiver">quiver</a>(U, V, **kw)<br>
<a href="#Axes-quiver">quiver</a>(U, V, C, **kw)<br>
<a href="#Axes-quiver">quiver</a>(X, Y, U, V, **kw)<br>
<a href="#Axes-quiver">quiver</a>(X, Y, U, V, C, **kw)<br>
<br>
Arguments:<br>
<br>
X, Y give the x and y coordinates of the arrow locations<br>
(default is tail of arrow; see 'pivot' kwarg)<br>
U, V give the x and y components of the arrow vectors<br>
C is an optional array used to map colors to the arrows<br>
<br>
All arguments may be 1-D or 2-D arrays or sequences.<br>
If X and Y are absent, they will be generated as a uniform grid.<br>
If U and V are 2-D arrays but X and Y are 1-D, and if<br>
len(X) and len(Y) match the column and row dimensions<br>
of U, then X and Y will be expanded with meshgrid.<br>
<br>
Keyword arguments (default given first):<br>
<br>
* units = 'width' | 'height' | 'dots' | 'inches' | 'x' | 'y'<br>
arrow units; the arrow dimensions *except for length*<br>
are in multiples of this unit.<br>
* scale = None | float<br>
data units per arrow unit, e.g. m/s per plot width;<br>
a smaller scale parameter makes the arrow longer.<br>
If None, a simple autoscaling algorithm is used, based<br>
on the average vector length and the number of vectors.<br>
<br>
Arrow dimensions and scales can be in any of several units:<br>
<br>
'width' or 'height': the width or height of the axes<br>
'dots' or 'inches': pixels or inches, based on the figure dpi<br>
'x' or 'y': X or Y data units<br>
<br>
In all cases the arrow aspect ratio is 1, so that if U==V the angle<br>
of the arrow on the plot is 45 degrees CCW from the X-axis.<br>
<br>
The arrows scale differently depending on the units, however.<br>
For 'x' or 'y', the arrows get larger as one zooms in; for other<br>
units, the arrow size is independent of the zoom state. For<br>
'width or 'height', the arrow size increases with the width and<br>
height of the axes, respectively, when the the window is resized;<br>
for 'dots' or 'inches', resizing does not change the arrows.<br>
<br>
<br>
* width = ? shaft width in arrow units; default depends on<br>
choice of units, above, and number of vectors;<br>
a typical starting value is about<br>
0.005 times the width of the plot.<br>
* headwidth = 3 head width as multiple of shaft width<br>
* headlength = 5 head length as multiple of shaft width<br>
* headaxislength = 4.5 head length at shaft intersection<br>
* minshaft = 1 length below which arrow scales, in units<br>
of head length. Do not set this to less<br>
than 1, or small arrows will look terrible!<br>
* minlength = 1 minimum length as a multiple of shaft width;<br>
if an arrow length is less than this, plot a<br>
dot (hexagon) of this diameter instead.<br>
<br>
The defaults give a slightly swept-back arrow; to make the<br>
head a triangle, make headaxislength the same as headlength.<br>
To make the arrow more pointed, reduce headwidth or increase<br>
headlength and headaxislength.<br>
To make the head smaller relative to the shaft, scale down<br>
all the head* parameters.<br>
You will probably do best to leave minshaft alone.<br>
<br>
* pivot = 'tail' | 'middle' | 'tip'<br>
The part of the arrow that is at the grid point; the arrow<br>
rotates about this point, hence the name 'pivot'.<br>
<br>
* color = 'k' | any matplotlib color spec or sequence of color specs.<br>
This is a synonym for the PolyCollection facecolor kwarg.<br>
If C has been set, 'color' has no effect.<br>
<br>
* All PolyCollection kwargs are valid, in the sense that they<br>
will be passed on to the PolyCollection constructor.<br>
In particular, one might want to use, for example:<br>
linewidths = (1,), edgecolors = ('g',)<br>
to make the arrows have green outlines of unit width.</tt></dd></dl>
<dl><dt><a name="Axes-quiver2"><strong>quiver2</strong></a>(self, *args, **kw)</dt><dd><tt>Plot a 2-D field of arrows.<br>
<br>
Function signatures:<br>
<br>
<a href="#Axes-quiver">quiver</a>(U, V, **kw)<br>
<a href="#Axes-quiver">quiver</a>(U, V, C, **kw)<br>
<a href="#Axes-quiver">quiver</a>(X, Y, U, V, **kw)<br>
<a href="#Axes-quiver">quiver</a>(X, Y, U, V, C, **kw)<br>
<br>
Arguments:<br>
<br>
X, Y give the x and y coordinates of the arrow locations<br>
(default is tail of arrow; see 'pivot' kwarg)<br>
U, V give the x and y components of the arrow vectors<br>
C is an optional array used to map colors to the arrows<br>
<br>
All arguments may be 1-D or 2-D arrays or sequences.<br>
If X and Y are absent, they will be generated as a uniform grid.<br>
If U and V are 2-D arrays but X and Y are 1-D, and if<br>
len(X) and len(Y) match the column and row dimensions<br>
of U, then X and Y will be expanded with meshgrid.<br>
<br>
Keyword arguments (default given first):<br>
<br>
* units = 'width' | 'height' | 'dots' | 'inches' | 'x' | 'y'<br>
arrow units; the arrow dimensions *except for length*<br>
are in multiples of this unit.<br>
* scale = None | float<br>
data units per arrow unit, e.g. m/s per plot width;<br>
a smaller scale parameter makes the arrow longer.<br>
If None, a simple autoscaling algorithm is used, based<br>
on the average vector length and the number of vectors.<br>
<br>
Arrow dimensions and scales can be in any of several units:<br>
<br>
'width' or 'height': the width or height of the axes<br>
'dots' or 'inches': pixels or inches, based on the figure dpi<br>
'x' or 'y': X or Y data units<br>
<br>
In all cases the arrow aspect ratio is 1, so that if U==V the angle<br>
of the arrow on the plot is 45 degrees CCW from the X-axis.<br>
<br>
The arrows scale differently depending on the units, however.<br>
For 'x' or 'y', the arrows get larger as one zooms in; for other<br>
units, the arrow size is independent of the zoom state. For<br>
'width or 'height', the arrow size increases with the width and<br>
height of the axes, respectively, when the the window is resized;<br>
for 'dots' or 'inches', resizing does not change the arrows.<br>
<br>
<br>
* width = ? shaft width in arrow units; default depends on<br>
choice of units, above, and number of vectors;<br>
a typical starting value is about<br>
0.005 times the width of the plot.<br>
* headwidth = 3 head width as multiple of shaft width<br>
* headlength = 5 head length as multiple of shaft width<br>
* headaxislength = 4.5 head length at shaft intersection<br>
* minshaft = 1 length below which arrow scales, in units<br>
of head length. Do not set this to less<br>
than 1, or small arrows will look terrible!<br>
* minlength = 1 minimum length as a multiple of shaft width;<br>
if an arrow length is less than this, plot a<br>
dot (hexagon) of this diameter instead.<br>
<br>
The defaults give a slightly swept-back arrow; to make the<br>
head a triangle, make headaxislength the same as headlength.<br>
To make the arrow more pointed, reduce headwidth or increase<br>
headlength and headaxislength.<br>
To make the head smaller relative to the shaft, scale down<br>
all the head* parameters.<br>
You will probably do best to leave minshaft alone.<br>
<br>
* pivot = 'tail' | 'middle' | 'tip'<br>
The part of the arrow that is at the grid point; the arrow<br>
rotates about this point, hence the name 'pivot'.<br>
<br>
* color = 'k' | any matplotlib color spec or sequence of color specs.<br>
This is a synonym for the PolyCollection facecolor kwarg.<br>
If C has been set, 'color' has no effect.<br>
<br>
* All PolyCollection kwargs are valid, in the sense that they<br>
will be passed on to the PolyCollection constructor.<br>
In particular, one might want to use, for example:<br>
linewidths = (1,), edgecolors = ('g',)<br>
to make the arrows have green outlines of unit width.</tt></dd></dl>
<dl><dt><a name="Axes-quiver_classic"><strong>quiver_classic</strong></a>(self, U, V, *args, **kwargs)</dt><dd><tt>QUIVER( X, Y, U, V )<br>
QUIVER( U, V )<br>
QUIVER( X, Y, U, V, S)<br>
QUIVER( U, V, S )<br>
QUIVER( ..., color=None, width=1.0, cmap=None, norm=None )<br>
<br>
Make a vector plot (U, V) with arrows on a grid (X, Y)<br>
<br>
If X and Y are not specified, U and V must be 2D arrays. Equally spaced<br>
X and Y grids are then generated using the meshgrid command.<br>
<br>
color can be a color value or an array of colors, so that the arrows can be<br>
colored according to another dataset. If cmap is specified and color is 'length',<br>
the colormap is used to give a color according to the vector's length.<br>
<br>
If color is a scalar field, the colormap is used to map the scalar to a color<br>
If a colormap is specified and color is an array of color triplets, then the<br>
colormap is ignored<br>
<br>
width is a scalar that controls the width of the arrows<br>
<br>
if S is specified it is used to scale the vectors. Use S=0 to disable automatic<br>
scaling.<br>
If S!=0, vectors are scaled to fit within the grid and then are multiplied by S.</tt></dd></dl>
<dl><dt><a name="Axes-quiverkey"><strong>quiverkey</strong></a>(self, *args, **kw)</dt><dd><tt>Add a key to a quiver plot.<br>
<br>
Function signature:<br>
<a href="#Axes-quiverkey">quiverkey</a>(Q, X, Y, U, label, **kw)<br>
<br>
Arguments:<br>
Q is the Quiver instance returned by a call to quiver.<br>
X, Y give the location of the key; additional explanation follows.<br>
U is the length of the key<br>
label is a string with the length and units of the key<br>
<br>
Keyword arguments (default given first):<br>
* coordinates = 'axes' | 'figure' | 'data' | 'inches'<br>
Coordinate system and units for X, Y: 'axes' and 'figure'<br>
are normalized coordinate systems with 0,0 in the lower<br>
left and 1,1 in the upper right; 'data' are the axes<br>
data coordinates (used for the locations of the vectors<br>
in the quiver plot itself); 'inches' is position in the<br>
figure in inches, with 0,0 at the lower left corner.<br>
* color overrides face and edge colors from Q.<br>
* labelpos = 'N' | 'S' | 'E' | 'W'<br>
Position the label above, below, to the right, to the left<br>
of the arrow, respectively.<br>
* labelsep = 0.1 inches distance between the arrow and the label<br>
* labelcolor (defaults to default Text color)<br>
* fontproperties is a dictionary with keyword arguments accepted<br>
by the FontProperties initializer: family, style, variant,<br>
size, weight<br>
<br>
Any additional keyword arguments are used to override vector<br>
properties taken from Q.<br>
<br>
The positioning of the key depends on X, Y, coordinates, and<br>
labelpos. If labelpos is 'N' or 'S', X,Y give the position<br>
of the middle of the key arrow. If labelpos is 'E', X,Y<br>
positions the head, and if labelpos is 'W', X,Y positions the<br>
tail; in either of these two cases, X,Y is somewhere in the middle<br>
of the arrow+label key object.</tt></dd></dl>
<dl><dt><a name="Axes-redraw_in_frame"><strong>redraw_in_frame</strong></a>(self)</dt><dd><tt>This method can only be used after an initial draw which<br>
caches the renderer. It is used to efficiently update <a href="#Axes">Axes</a><br>
data (axis ticks, labels, etc are not updated)</tt></dd></dl>
<dl><dt><a name="Axes-relim"><strong>relim</strong></a>(self)</dt><dd><tt>recompute the datalimits based on current artists</tt></dd></dl>
<dl><dt><a name="Axes-scatter"><strong>scatter</strong></a>(self, x, y, s<font color="#909090">=20</font>, c<font color="#909090">='b'</font>, marker<font color="#909090">='o'</font>, cmap<font color="#909090">=None</font>, norm<font color="#909090">=None</font>, vmin<font color="#909090">=None</font>, vmax<font color="#909090">=None</font>, alpha<font color="#909090">=1.0</font>, linewidths<font color="#909090">=None</font>, faceted<font color="#909090">=True</font>, verts<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SCATTER(x, y, s=20, c='b', marker='o', cmap=None, norm=None,<br>
vmin=None, vmax=None, alpha=1.0, linewidths=None,<br>
faceted=True, **kwargs)<br>
Supported function signatures:<br>
SCATTER(x, y, **kwargs)<br>
SCATTER(x, y, s, **kwargs)<br>
SCATTER(x, y, s, c, **kwargs)<br>
Make a scatter plot of x versus y, where x, y are 1-D sequences<br>
of the same length, N.<br>
Arguments s and c can also be given as kwargs; this is encouraged<br>
for readability.<br>
s is a size in points^2. It is a scalar<br>
or an array of the same length as x and y.<br>
c is a color and can be a single color format string,<br>
or a sequence of color specifications of length N,<br>
or a sequence of N numbers to be mapped to colors<br>
using the cmap and norm specified via kwargs (see below).<br>
Note that c should not be a single numeric RGB or RGBA<br>
sequence because that is indistinguishable from an array<br>
of values to be colormapped. c can be a 2-D array in which<br>
the rows are RGB or RGBA, however.<br>
The marker can be one of<br>
's' : square<br>
'o' : circle<br>
'^' : triangle up<br>
'>' : triangle right<br>
'v' : triangle down<br>
'<' : triangle left<br>
'd' : diamond<br>
'p' : pentagram<br>
'h' : hexagon<br>
'8' : octagon<br>
If marker is None and verts is not None, verts is a sequence<br>
of (x,y) vertices for a custom scatter symbol.<br>
s is a size argument in points squared.<br>
Any or all of x, y, s, and c may be masked arrays, in which<br>
case all masks will be combined and only unmasked points<br>
will be plotted.<br>
Other keyword args; the color mapping and normalization arguments will<br>
on be used if c is an array of floats<br>
* cmap = cm.jet : a colors.Colormap instance from matplotlib.cm.<br>
defaults to rc image.cmap<br>
* norm = Normalize() : matplotlib.colors.Normalize instance<br>
is used to scale luminance data to 0,1.<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used. Note if you pass a norm<br>
instance, your settings for vmin and vmax will be ignored<br>
* alpha =1.0 : the alpha value for the patches<br>
* linewidths, if None, defaults to (lines.linewidth,). Note<br>
that this is a tuple, and if you set the linewidths<br>
argument you must set it as a sequence of floats, as<br>
required by RegularPolyCollection -- see<br>
matplotlib.collections.RegularPolyCollection for details<br>
* faceted: if True, will use the default edgecolor for the<br>
markers. If False, will set the edgecolors to be the same<br>
as the facecolors<br>
Optional kwargs control the PatchCollection properties:<br>
alpha: float<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
edgecolor: matplotlib color arg or sequence of rgba tuples<br>
facecolor: matplotlib color arg or sequence of rgba tuples<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-scatter_classic"><strong>scatter_classic</strong></a>(self, x, y, s<font color="#909090">=None</font>, c<font color="#909090">='b'</font>)</dt><dd><tt>scatter_classic is no longer available; please use scatter.<br>
To help in porting, for comparison to the scatter docstring,<br>
here is the scatter_classic docstring:<br>
<br>
SCATTER_CLASSIC(x, y, s=None, c='b')<br>
<br>
Make a scatter plot of x versus y. s is a size (in data coords) and<br>
can be either a scalar or an array of the same length as x or y. c is<br>
a color and can be a single color format string or an length(x) array<br>
of intensities which will be mapped by the colormap jet.<br>
<br>
If size is None a default size will be used</tt></dd></dl>
<dl><dt><a name="Axes-semilogx"><strong>semilogx</strong></a>(self, *args, **kwargs)</dt><dd><tt>SEMILOGX(*args, **kwargs)<br>
Make a semilog plot with log scaling on the x axis. The args to<br>
semilog x are the same as the args to plot. See help plot for more<br>
info.<br>
Optional keyword args supported are any of the kwargs supported by<br>
plot or set_xscale. Notable, for log scaling:<br>
* basex: base of the logarithm<br>
* subsx: the location of the minor ticks; None defaults to<br>
autosubs, which depend on the number of decades in the<br>
plot; see set_xscale for details<br>
The remaining valid kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-semilogy"><strong>semilogy</strong></a>(self, *args, **kwargs)</dt><dd><tt>SEMILOGY(*args, **kwargs):<br>
Make a semilog plot with log scaling on the y axis. The args to<br>
semilogy are the same as the args to plot. See help plot for more<br>
info.<br>
Optional keyword args supported are any of the kwargs supported by<br>
plot or set_yscale. Notable, for log scaling:<br>
* basey: base of the logarithm<br>
* subsy: a sequence of the location of the minor ticks;<br>
None defaults to autosubs, which depend on the number of<br>
decades in the plot; see set_yscale for details<br>
The remaining valid kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-set_adjustable"><strong>set_adjustable</strong></a>(self, adjustable)</dt><dd><tt>ACCEPTS: ['box' | 'datalim']</tt></dd></dl>
<dl><dt><a name="Axes-set_anchor"><strong>set_anchor</strong></a>(self, anchor)</dt><dd><tt>ACCEPTS: ['C', 'SW', 'S', 'SE', 'E', 'NE', 'N', 'NW', 'W']</tt></dd></dl>
<dl><dt><a name="Axes-set_aspect"><strong>set_aspect</strong></a>(self, aspect, adjustable<font color="#909090">=None</font>, anchor<font color="#909090">=None</font>)</dt><dd><tt>aspect:<br>
'auto' - automatic; fill position rectangle with data<br>
'normal' - same as 'auto'; deprecated<br>
'equal' - same scaling from data to plot units for x and y<br>
num - a circle will be stretched such that the height<br>
is num times the width. aspect=1 is the same as<br>
aspect='equal'.<br>
<br>
adjustable:<br>
'box' - change physical size of axes<br>
'datalim' - change xlim or ylim<br>
<br>
anchor:<br>
'C' - centered<br>
'SW' - lower left corner<br>
'S' - middle of bottom edge<br>
'SE' - lower right corner<br>
etc.<br>
<br>
ACCEPTS: ['auto' | 'equal' | aspect_ratio]</tt></dd></dl>
<dl><dt><a name="Axes-set_autoscale_on"><strong>set_autoscale_on</strong></a>(self, b)</dt><dd><tt>Set whether autoscaling is applied on plot commands<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="Axes-set_axis_bgcolor"><strong>set_axis_bgcolor</strong></a>(self, color)</dt><dd><tt>set the axes background color<br>
<br>
ACCEPTS: any matplotlib color - see help(colors)</tt></dd></dl>
<dl><dt><a name="Axes-set_axis_off"><strong>set_axis_off</strong></a>(self)</dt><dd><tt>turn off the axis<br>
<br>
ACCEPTS: void</tt></dd></dl>
<dl><dt><a name="Axes-set_axis_on"><strong>set_axis_on</strong></a>(self)</dt><dd><tt>turn on the axis<br>
<br>
ACCEPTS: void</tt></dd></dl>
<dl><dt><a name="Axes-set_axisbelow"><strong>set_axisbelow</strong></a>(self, b)</dt><dd><tt>Set whether the axis ticks and gridlines are above or below most artists<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="Axes-set_cursor_props"><strong>set_cursor_props</strong></a>(self, *args)</dt><dd><tt>Set the cursor property as<br>
ax.<a href="#Axes-set_cursor_props">set_cursor_props</a>(linewidth, color) OR<br>
ax.<a href="#Axes-set_cursor_props">set_cursor_props</a>((linewidth, color))<br>
<br>
ACCEPTS: a (float, color) tuple</tt></dd></dl>
<dl><dt><a name="Axes-set_figure"><strong>set_figure</strong></a>(self, fig)</dt><dd><tt>Set the <a href="#Axes">Axes</a> figure<br>
<br>
ACCEPTS: a Figure instance</tt></dd></dl>
<dl><dt><a name="Axes-set_frame_on"><strong>set_frame_on</strong></a>(self, b)</dt><dd><tt>Set whether the axes rectangle patch is drawn<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="Axes-set_navigate"><strong>set_navigate</strong></a>(self, b)</dt><dd><tt>Set whether the axes responds to navigation toolbar commands<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="Axes-set_navigate_mode"><strong>set_navigate_mode</strong></a>(self, b)</dt><dd><tt>Set the navigation toolbar button status;<br>
this is not a user-API function.</tt></dd></dl>
<dl><dt><a name="Axes-set_position"><strong>set_position</strong></a>(self, pos, which<font color="#909090">='both'</font>)</dt><dd><tt>Set the axes position with pos = [left, bottom, width, height]<br>
in relative 0,1 coords<br>
<br>
There are two position variables: one which is ultimately<br>
used, but which may be modified by apply_aspect, and a second<br>
which is the starting point for apply_aspect.<br>
<br>
which = 'active' to change the first;<br>
'original' to change the second;<br>
'both' to change both<br>
<br>
ACCEPTS: len(4) sequence of floats</tt></dd></dl>
<dl><dt><a name="Axes-set_title"><strong>set_title</strong></a>(self, label, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_TITLE(label, fontdict=None, **kwargs):<br>
Set the title for the axes. See the text docstring for information<br>
of how override and the optional args work<br>
kwargs are Text properties:<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="Axes-set_xlabel"><strong>set_xlabel</strong></a>(self, xlabel, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_XLABEL(xlabel, fontdict=None, **kwargs)<br>
Set the label for the xaxis. See the text docstring for information<br>
of how override and the optional args work.<br>
Valid kwargs are Text properties:<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="Axes-set_xlim"><strong>set_xlim</strong></a>(self, xmin<font color="#909090">=None</font>, xmax<font color="#909090">=None</font>, emit<font color="#909090">=False</font>, **kwargs)</dt><dd><tt><a href="#Axes-set_xlim">set_xlim</a>(self, *args, **kwargs):<br>
<br>
Set the limits for the xaxis; v = [xmin, xmax]<br>
<br>
<a href="#Axes-set_xlim">set_xlim</a>((valmin, valmax))<br>
<a href="#Axes-set_xlim">set_xlim</a>(valmin, valmax)<br>
<a href="#Axes-set_xlim">set_xlim</a>(xmin=1) # xmax unchanged<br>
<a href="#Axes-set_xlim">set_xlim</a>(xmax=1) # xmin unchanged<br>
<br>
Valid kwargs:<br>
<br>
xmin : the min of the xlim<br>
xmax : the max of the xlim<br>
emit : notify observers of lim change<br>
<br>
<br>
Returns the current xlimits as a length 2 tuple<br>
<br>
ACCEPTS: len(2) sequence of floats</tt></dd></dl>
<dl><dt><a name="Axes-set_xscale"><strong>set_xscale</strong></a>(self, value, basex<font color="#909090">=10</font>, subsx<font color="#909090">=None</font>)</dt><dd><tt>SET_XSCALE(value, basex=10, subsx=None)<br>
<br>
Set the xscaling: 'log' or 'linear'<br>
<br>
If value is 'log', the additional kwargs have the following meaning<br>
<br>
* basex: base of the logarithm<br>
<br>
* subsx: a sequence of the location of the minor ticks;<br>
None defaults to autosubs, which depend on the number of<br>
decades in the plot. Eg for base 10, subsx=(1,2,5) will<br>
put minor ticks on 1,2,5,11,12,15,21, ....To turn off<br>
minor ticking, set subsx=[]<br>
<br>
ACCEPTS: ['log' | 'linear' ]</tt></dd></dl>
<dl><dt><a name="Axes-set_xticklabels"><strong>set_xticklabels</strong></a>(self, labels, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_XTICKLABELS(labels, fontdict=None, **kwargs)<br>
Set the xtick labels with list of strings labels Return a list of axis<br>
text instances.<br>
kwargs set the Text properties. Valid properties are<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: sequence of strings</tt></dd></dl>
<dl><dt><a name="Axes-set_xticks"><strong>set_xticks</strong></a>(self, ticks)</dt><dd><tt>Set the x ticks with list of ticks<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="Axes-set_ylabel"><strong>set_ylabel</strong></a>(self, ylabel, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_YLABEL(ylabel, fontdict=None, **kwargs)<br>
Set the label for the yaxis<br>
See the text doctstring for information of how override and<br>
the optional args work<br>
Valid kwargs are Text properties:<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="Axes-set_ylim"><strong>set_ylim</strong></a>(self, ymin<font color="#909090">=None</font>, ymax<font color="#909090">=None</font>, emit<font color="#909090">=False</font>, **kwargs)</dt><dd><tt><a href="#Axes-set_ylim">set_ylim</a>(self, *args, **kwargs):<br>
<br>
Set the limits for the yaxis; v = [ymin, ymax]<br>
<br>
<a href="#Axes-set_ylim">set_ylim</a>((valmin, valmax))<br>
<a href="#Axes-set_ylim">set_ylim</a>(valmin, valmax)<br>
<a href="#Axes-set_ylim">set_ylim</a>(ymin=1) # ymax unchanged<br>
<a href="#Axes-set_ylim">set_ylim</a>(ymax=1) # ymin unchanged<br>
<br>
Valid kwargs:<br>
<br>
ymin : the min of the ylim<br>
ymax : the max of the ylim<br>
emit : notify observers of lim change<br>
<br>
Returns the current ylimits as a length 2 tuple<br>
<br>
ACCEPTS: len(2) sequence of floats</tt></dd></dl>
<dl><dt><a name="Axes-set_yscale"><strong>set_yscale</strong></a>(self, value, basey<font color="#909090">=10</font>, subsy<font color="#909090">=None</font>)</dt><dd><tt>SET_YSCALE(value, basey=10, subsy=None)<br>
<br>
Set the yscaling: 'log' or 'linear'<br>
<br>
If value is 'log', the additional kwargs have the following meaning<br>
<br>
* basey: base of the logarithm<br>
<br>
* subsy: a sequence of the location of the minor ticks;<br>
None defaults to autosubs, which depend on the number of<br>
decades in the plot. Eg for base 10, subsy=(1,2,5) will<br>
put minor ticks on 1,2,5,11,12,15, 21, ....To turn off<br>
minor ticking, set subsy=[]<br>
<br>
ACCEPTS: ['log' | 'linear']</tt></dd></dl>
<dl><dt><a name="Axes-set_yticklabels"><strong>set_yticklabels</strong></a>(self, labels, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_YTICKLABELS(labels, fontdict=None, **kwargs)<br>
Set the ytick labels with list of strings labels. Return a list of<br>
Text instances.<br>
kwargs set Text properties for the labels. Valid properties are<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: sequence of strings</tt></dd></dl>
<dl><dt><a name="Axes-set_yticks"><strong>set_yticks</strong></a>(self, ticks)</dt><dd><tt>Set the y ticks with list of ticks<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="Axes-specgram"><strong>specgram</strong></a>(self, x, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, window<font color="#909090">=<function window_hanning at 0xb5bc7764></font>, noverlap<font color="#909090">=128</font>, cmap<font color="#909090">=None</font>, xextent<font color="#909090">=None</font>)</dt><dd><tt>SPECGRAM(x, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=128,<br>
cmap=None, xextent=None)<br>
<br>
Compute a spectrogram of data in x. Data are split into NFFT length<br>
segements and the PSD of each section is computed. The windowing<br>
function window is applied to each segment, and the amount of overlap<br>
of each segment is specified with noverlap.<br>
<br>
* cmap is a colormap; if None use default determined by rc<br>
<br>
* xextent is the image extent in the xaxes xextent=xmin, xmax -<br>
default 0, max(bins), 0, max(freqs) where bins is the return<br>
value from matplotlib.matplotlib.mlab.specgram<br>
<br>
* See help(psd) for information on the other keyword arguments.<br>
<br>
Return value is (Pxx, freqs, bins, im), where<br>
<br>
bins are the time points the spectrogram is calculated over<br>
<br>
freqs is an array of frequencies<br>
<br>
Pxx is a len(times) x len(freqs) array of power<br>
<br>
im is a matplotlib.image.AxesImage.<br>
<br>
Note: If x is real (i.e. non-complex) only the positive spectrum is<br>
shown. If x is complex both positive and negative parts of the<br>
spectrum are shown.</tt></dd></dl>
<dl><dt><a name="Axes-spy"><strong>spy</strong></a>(self, Z, precision<font color="#909090">=None</font>, marker<font color="#909090">=None</font>, markersize<font color="#909090">=None</font>, aspect<font color="#909090">='equal'</font>, **kwargs)</dt><dd><tt><a href="#Axes-spy">spy</a>(Z) plots the sparsity pattern of the 2-D array Z<br>
<br>
If precision is None, any non-zero value will be plotted;<br>
else, values of absolute(Z)>precision will be plotted.<br>
<br>
The array will be plotted as it would be printed, with<br>
the first index (row) increasing down and the second<br>
index (column) increasing to the right.<br>
<br>
By default aspect is 'equal' so that each array element<br>
occupies a square space; set the aspect kwarg to 'auto'<br>
to allow the plot to fill the plot box, or to any scalar<br>
number to specify the aspect ratio of an array element<br>
directly.<br>
<br>
Two plotting styles are available: image or marker. Both<br>
are available for full arrays, but only the marker style<br>
works for scipy.sparse.spmatrix instances.<br>
<br>
If marker and markersize are None, an image will be<br>
returned and any remaining kwargs are passed to imshow;<br>
else, a Line2D object will be returned with the value<br>
of marker determining the marker type, and any remaining<br>
kwargs passed to the axes plot method.<br>
<br>
If marker and markersize are None, useful kwargs include:<br>
cmap<br>
alpha<br>
See documentation for <a href="#Axes-imshow">imshow</a>() for details.<br>
For controlling colors, e.g. cyan background and red marks, use:<br>
cmap = matplotlib.colors.ListedColormap(['c','r'])<br>
<br>
If marker or markersize is not None, useful kwargs include:<br>
marker<br>
markersize<br>
color<br>
See documentation for <a href="#Axes-plot">plot</a>() for details.<br>
<br>
Useful values for marker include:<br>
's' square (default)<br>
'o' circle<br>
'.' point<br>
',' pixel</tt></dd></dl>
<dl><dt><a name="Axes-stem"><strong>stem</strong></a>(self, x, y, linefmt<font color="#909090">='b-'</font>, markerfmt<font color="#909090">='bo'</font>, basefmt<font color="#909090">='r-'</font>)</dt><dd><tt>STEM(x, y, linefmt='b-', markerfmt='bo', basefmt='r-')<br>
<br>
A stem plot plots vertical lines (using linefmt) at each x location<br>
from the baseline to y, and places a marker there using markerfmt. A<br>
horizontal line at 0 is is plotted using basefmt<br>
<br>
Return value is (markerline, stemlines, baseline) .<br>
<br>
See<br>
<a href="http://www.mathworks.com/access/helpdesk/help/techdoc/ref/stem.html">http://www.mathworks.com/access/helpdesk/help/techdoc/ref/stem.html</a><br>
for details and examples/stem_plot.py for a demo.</tt></dd></dl>
<dl><dt><a name="Axes-table"><strong>table</strong></a>(self, **kwargs)</dt><dd><tt>TABLE(cellText=None, cellColours=None,<br>
cellLoc='right', colWidths=None,<br>
rowLabels=None, rowColours=None, rowLoc='left',<br>
colLabels=None, colColours=None, colLoc='center',<br>
loc='bottom', bbox=None):<br>
Add a table to the current axes. Returns a table instance. For<br>
finer grained control over tables, use the Table class and add it<br>
to the axes with add_table.<br>
Thanks to John Gill for providing the class and table.<br>
kwargs control the Table properties:<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
figure: a matplotlib.figure.Figure instance<br>
fontsize: a float in points<br>
label: any string<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-text"><strong>text</strong></a>(self, x, y, s, fontdict<font color="#909090">=None</font>, withdash<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>TEXT(x, y, s, fontdict=None, **kwargs)<br>
Add text in string s to axis at location x,y (data coords)<br>
fontdict is a dictionary to override the default text properties.<br>
If fontdict is None, the defaults are determined by your rc<br>
parameters.<br>
withdash=True will create a TextWithDash instance instead<br>
of a Text instance.<br>
Individual keyword arguments can be used to override any given<br>
parameter<br>
<a href="#Axes-text">text</a>(x, y, s, fontsize=12)<br>
The default transform specifies that text is in data coords,<br>
alternatively, you can specify text in axis coords (0,0 lower left and<br>
1,1 upper right). The example below places text in the center of the<br>
axes<br>
<a href="#Axes-text">text</a>(0.5, 0.5,'matplotlib',<br>
horizontalalignment='center',<br>
verticalalignment='center',<br>
transform = ax.transAxes,<br>
)<br>
You can put a rectangular box around the text instance (eg to<br>
set a background color) by using the keyword bbox. bbox is a<br>
dictionary of matplotlib.patches.Rectangle properties (see help<br>
for Rectangle for a list of these). For example<br>
<a href="#Axes-text">text</a>(x, y, s, bbox=dict(facecolor='red', alpha=0.5))<br>
Valid kwargs are Text properties<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-ticklabel_format"><strong>ticklabel_format</strong></a>(self, **kwargs)</dt><dd><tt>Convenience method for manipulating the ScalarFormatter<br>
used by default for linear axes.<br>
<br>
kwargs:<br>
style = 'sci' (or 'scientific') or 'plain';<br>
plain turns off scientific notation<br>
axis = 'x', 'y', or 'both'<br>
<br>
Only the major ticks are affected.<br>
If the method is called when the ScalarFormatter is not<br>
the one being used, an AttributeError will be raised with<br>
no additional error message.<br>
<br>
Additional capabilities and/or friendlier error checking may be added.</tt></dd></dl>
<dl><dt><a name="Axes-toggle_log_lineary"><strong>toggle_log_lineary</strong></a>(self)</dt><dd><tt>toggle between log and linear on the y axis</tt></dd></dl>
<dl><dt><a name="Axes-update_datalim"><strong>update_datalim</strong></a>(self, xys)</dt><dd><tt>Update the data lim bbox with seq of xy tups or equiv. 2-D array</tt></dd></dl>
<dl><dt><a name="Axes-update_datalim_numerix"><strong>update_datalim_numerix</strong></a>(self, x, y)</dt><dd><tt>Update the data lim bbox with seq of xy tups</tt></dd></dl>
<dl><dt><a name="Axes-vlines"><strong>vlines</strong></a>(self, x, ymin, ymax, colors<font color="#909090">='k'</font>, linestyle<font color="#909090">='solid'</font>, label<font color="#909090">=''</font>, **kwargs)</dt><dd><tt>VLINES(x, ymin, ymax, color='k')<br>
Plot vertical lines at each x from ymin to ymax. ymin or ymax can be<br>
scalars or len(x) numpy arrays. If they are scalars, then the<br>
respective values are constant, else the heights of the lines are<br>
determined by ymin and ymax<br>
colors is a line collections color args, either a single color<br>
or a len(x) list of colors<br>
linestyle is one of solid|dashed|dashdot|dotted<br>
Returns the LineCollection that was added<br>
kwargs are LineCollection properties:<br>
alpha: float or sequence of floats<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle: ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
segments: unknown<br>
transform: a matplotlib.transform transformation instance<br>
verts: unknown<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Axes-xaxis_date"><strong>xaxis_date</strong></a>(self, tz<font color="#909090">=None</font>)</dt><dd><tt>Sets up x-axis ticks and labels that treat the x data as dates.<br>
<br>
tz is the time zone to use in labeling dates. Defaults to rc value.</tt></dd></dl>
<dl><dt><a name="Axes-xcorr"><strong>xcorr</strong></a>(self, x, y, normed<font color="#909090">=False</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, usevlines<font color="#909090">=False</font>, maxlags<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>XCORR(x, y, normed=False, detrend=detrend_none, usevlines=False, **kwargs):<br>
Plot the cross correlation between x and y. If normed=True,<br>
normalize the data but the cross correlation at 0-th lag. x<br>
and y are detrended by the detrend callable (default no<br>
normalization. x and y must be equal length<br>
data are plotted as <a href="#Axes-plot">plot</a>(lags, c, **kwargs)<br>
return value is lags, c, line where lags are a length<br>
2*maxlags+1 lag vector, c is the 2*maxlags+1 auto correlation<br>
vector, and line is a Line2D instance returned by plot. The<br>
default linestyle is None and the default marker is 'o',<br>
though these can be overridden with keyword args. The cross<br>
correlation is performed with numerix cross_correlate with<br>
mode=2.<br>
If usevlines is True, <a href="#Axes">Axes</a>.vlines rather than <a href="#Axes">Axes</a>.plot is used<br>
to draw vertical lines from the origin to the acorr.<br>
Otherwise the plotstyle is determined by the kwargs, which are<br>
Line2D properties. If usevlines, the return value is lags, c,<br>
linecol, b where linecol is the LineCollection and b is the x-axis<br>
if usevlines=True, kwargs are passed onto <a href="#Axes">Axes</a>.vlines<br>
if usevlines=False, kwargs are passed onto <a href="#Axes">Axes</a>.plot<br>
maxlags is a positive integer detailing the number of lags to show.<br>
The default value of None will return all (2*len(x)-1) lags.<br>
See the respective function for documentation on valid kwargs</tt></dd></dl>
<dl><dt><a name="Axes-yaxis_date"><strong>yaxis_date</strong></a>(self, tz<font color="#909090">=None</font>)</dt><dd><tt>Sets up y-axis ticks and labels that treat the y data as dates.<br>
<br>
tz is the time zone to use in labeling dates. Defaults to rc value.</tt></dd></dl>
<dl><dt><a name="Axes-zoomx"><strong>zoomx</strong></a>(self, numsteps)</dt><dd><tt>Zoom in on the x xaxis numsteps (plus for zoom in, minus for zoom out)</tt></dd></dl>
<dl><dt><a name="Axes-zoomy"><strong>zoomy</strong></a>(self, numsteps)</dt><dd><tt>Zoom in on the x xaxis numsteps (plus for zoom in, minus for zoom out)</tt></dd></dl>
<hr>
Data and other attributes defined here:<br>
<dl><dt><strong>scaled</strong> = {0: 'linear', 1: 'log'}</dl>
<hr>
Methods inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><a name="Axes-add_callback"><strong>add_callback</strong></a>(self, func)</dt></dl>
<dl><dt><a name="Axes-convert_xunits"><strong>convert_xunits</strong></a>(self, x)</dt><dd><tt>for artists in an axes, if the xaxis as units support,<br>
convert x using xaxis unit type</tt></dd></dl>
<dl><dt><a name="Axes-convert_yunits"><strong>convert_yunits</strong></a>(self, y)</dt><dd><tt>for artists in an axes, if the yaxis as units support,<br>
convert y using yaxis unit type</tt></dd></dl>
<dl><dt><a name="Axes-get_alpha"><strong>get_alpha</strong></a>(self)</dt><dd><tt>Return the alpha value used for blending - not supported on all<br>
backends</tt></dd></dl>
<dl><dt><a name="Axes-get_animated"><strong>get_animated</strong></a>(self)</dt><dd><tt>return the artist's animated state</tt></dd></dl>
<dl><dt><a name="Axes-get_axes"><strong>get_axes</strong></a>(self)</dt><dd><tt>return the axes instance the artist resides in, or None</tt></dd></dl>
<dl><dt><a name="Axes-get_clip_box"><strong>get_clip_box</strong></a>(self)</dt><dd><tt>Return artist clipbox</tt></dd></dl>
<dl><dt><a name="Axes-get_clip_on"><strong>get_clip_on</strong></a>(self)</dt><dd><tt>Return whether artist uses clipping</tt></dd></dl>
<dl><dt><a name="Axes-get_clip_path"><strong>get_clip_path</strong></a>(self)</dt><dd><tt>Return artist clip path</tt></dd></dl>
<dl><dt><a name="Axes-get_figure"><strong>get_figure</strong></a>(self)</dt><dd><tt>return the figure instance</tt></dd></dl>
<dl><dt><a name="Axes-get_label"><strong>get_label</strong></a>(self)</dt></dl>
<dl><dt><a name="Axes-get_picker"><strong>get_picker</strong></a>(self)</dt><dd><tt>return the Pickeration instance used by this artist</tt></dd></dl>
<dl><dt><a name="Axes-get_transform"><strong>get_transform</strong></a>(self)</dt><dd><tt>return the Transformation instance used by this artist</tt></dd></dl>
<dl><dt><a name="Axes-get_visible"><strong>get_visible</strong></a>(self)</dt><dd><tt>return the artist's visiblity</tt></dd></dl>
<dl><dt><a name="Axes-get_zorder"><strong>get_zorder</strong></a>(self)</dt></dl>
<dl><dt><a name="Axes-have_units"><strong>have_units</strong></a>(self)</dt><dd><tt>return True if units are set on the x or y axes</tt></dd></dl>
<dl><dt><a name="Axes-is_figure_set"><strong>is_figure_set</strong></a>(self)</dt></dl>
<dl><dt><a name="Axes-is_transform_set"><strong>is_transform_set</strong></a>(self)</dt><dd><tt><a href="matplotlib.artist.html#Artist">Artist</a> has transform explicity let</tt></dd></dl>
<dl><dt><a name="Axes-pchanged"><strong>pchanged</strong></a>(self)</dt><dd><tt>fire event when property changed</tt></dd></dl>
<dl><dt><a name="Axes-pickable"><strong>pickable</strong></a>(self)</dt><dd><tt>return True if self is pickable</tt></dd></dl>
<dl><dt><a name="Axes-remove_callback"><strong>remove_callback</strong></a>(self, oid)</dt></dl>
<dl><dt><a name="Axes-set"><strong>set</strong></a>(self, **kwargs)</dt><dd><tt>A tkstyle set command, pass kwargs to set properties</tt></dd></dl>
<dl><dt><a name="Axes-set_alpha"><strong>set_alpha</strong></a>(self, alpha)</dt><dd><tt>Set the alpha value used for blending - not supported on<br>
all backends<br>
<br>
ACCEPTS: float</tt></dd></dl>
<dl><dt><a name="Axes-set_animated"><strong>set_animated</strong></a>(self, b)</dt><dd><tt>set the artist's animation state<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="Axes-set_axes"><strong>set_axes</strong></a>(self, axes)</dt><dd><tt>set the axes instance the artist resides in, if any<br>
<br>
ACCEPTS: an axes instance</tt></dd></dl>
<dl><dt><a name="Axes-set_clip_box"><strong>set_clip_box</strong></a>(self, clipbox)</dt><dd><tt>Set the artist's clip Bbox<br>
<br>
ACCEPTS: a matplotlib.transform.Bbox instance</tt></dd></dl>
<dl><dt><a name="Axes-set_clip_on"><strong>set_clip_on</strong></a>(self, b)</dt><dd><tt>Set whether artist uses clipping<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="Axes-set_clip_path"><strong>set_clip_path</strong></a>(self, path)</dt><dd><tt>Set the artist's clip path<br>
<br>
ACCEPTS: an agg.path_storage instance</tt></dd></dl>
<dl><dt><a name="Axes-set_label"><strong>set_label</strong></a>(self, s)</dt><dd><tt>Set the line label to s for auto legend<br>
<br>
ACCEPTS: any string</tt></dd></dl>
<dl><dt><a name="Axes-set_lod"><strong>set_lod</strong></a>(self, on)</dt><dd><tt>Set Level of Detail on or off. If on, the artists may examine<br>
things like the pixel width of the axes and draw a subset of<br>
their contents accordingly<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="Axes-set_picker"><strong>set_picker</strong></a>(self, picker)</dt><dd><tt>set the epsilon for picking used by this artist<br>
<br>
picker can be one of the following:<br>
<br>
None - picking is disabled for this artist (default)<br>
<br>
boolean - if True then picking will be enabled and the<br>
artist will fire a pick event if the mouse event is over<br>
the artist<br>
<br>
float - if picker is a number it is interpreted as an<br>
epsilon tolerance in points and the the artist will fire<br>
off an event if it's data is within epsilon of the mouse<br>
event. For some artists like lines and patch collections,<br>
the artist may provide additional data to the pick event<br>
that is generated, eg the indices of the data within<br>
epsilon of the pick event<br>
<br>
function - if picker is callable, it is a user supplied<br>
function which determines whether the artist is hit by the<br>
mouse event.<br>
<br>
hit, props = picker(artist, mouseevent)<br>
<br>
to determine the hit test. if the mouse event is over the<br>
artist, return hit=True and props is a dictionary of<br>
properties you want added to the PickEvent attributes<br>
<br>
ACCEPTS: [None|float|boolean|callable]</tt></dd></dl>
<dl><dt><a name="Axes-set_transform"><strong>set_transform</strong></a>(self, t)</dt><dd><tt>set the Transformation instance used by this artist<br>
<br>
ACCEPTS: a matplotlib.transform transformation instance</tt></dd></dl>
<dl><dt><a name="Axes-set_visible"><strong>set_visible</strong></a>(self, b)</dt><dd><tt>set the artist's visiblity<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="Axes-set_zorder"><strong>set_zorder</strong></a>(self, level)</dt><dd><tt>Set the zorder for the artist<br>
<br>
ACCEPTS: any number</tt></dd></dl>
<dl><dt><a name="Axes-update"><strong>update</strong></a>(self, props)</dt></dl>
<dl><dt><a name="Axes-update_from"><strong>update_from</strong></a>(self, other)</dt><dd><tt>copy properties from other to self</tt></dd></dl>
<hr>
Data and other attributes inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><strong>aname</strong> = 'Artist'</dl>
<dl><dt><strong>zorder</strong> = 0</dl>
</td></tr></table> <p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#ffc8d8">
<td colspan=3 valign=bottom> <br>
<font color="#000000" face="helvetica, arial"><a name="PolarAxes">class <strong>PolarAxes</strong></a>(<a href="matplotlib.axes.html#Axes">Axes</a>)</font></td></tr>
<tr bgcolor="#ffc8d8"><td rowspan=2><tt> </tt></td>
<td colspan=2><tt>Make a <a href="#PolarAxes">PolarAxes</a>. The rectangular bounding box of the axes is given by<br>
<br>
<br>
<a href="#PolarAxes">PolarAxes</a>(position=[left, bottom, width, height])<br>
<br>
where all the arguments are fractions in [0,1] which specify the<br>
fraction of the total figure window.<br>
<br>
axisbg is the color of the axis background<br>
<br>
Attributes:<br>
thetagridlines : a list of Line2D for the theta grids<br>
rgridlines : a list of Line2D for the radial grids<br>
thetagridlabels : a list of Text for the theta grid labels<br>
rgridlabels : a list of Text for the theta grid labels<br> </tt></td></tr>
<tr><td> </td>
<td width="100%"><dl><dt>Method resolution order:</dt>
<dd><a href="matplotlib.axes.html#PolarAxes">PolarAxes</a></dd>
<dd><a href="matplotlib.axes.html#Axes">Axes</a></dd>
<dd><a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a></dd>
</dl>
<hr>
Methods defined here:<br>
<dl><dt><a name="PolarAxes-__init__"><strong>__init__</strong></a>(self, *args, **kwarg)</dt><dd><tt>See <a href="#Axes">Axes</a> base class for args and kwargs documentation</tt></dd></dl>
<dl><dt><a name="PolarAxes-autoscale_view"><strong>autoscale_view</strong></a>(self, scalex<font color="#909090">=True</font>, scaley<font color="#909090">=True</font>)</dt><dd><tt>set the view limits to include all the data in the axes</tt></dd></dl>
<dl><dt><a name="PolarAxes-cla"><strong>cla</strong></a>(self)</dt><dd><tt>Clear the current axes</tt></dd></dl>
<dl><dt><a name="PolarAxes-draw"><strong>draw</strong></a>(self, renderer)</dt></dl>
<dl><dt><a name="PolarAxes-format_coord"><strong>format_coord</strong></a>(self, theta, r)</dt><dd><tt>return a format string formatting the coordinate</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_children"><strong>get_children</strong></a>(self)</dt><dd><tt>return a list of child artists</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_rmax"><strong>get_rmax</strong></a>(self)</dt><dd><tt>get the maximum radius in the view limits dimension</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_xscale"><strong>get_xscale</strong></a>(self)</dt><dd><tt>return the xaxis scale string</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_yscale"><strong>get_yscale</strong></a>(self)</dt><dd><tt>return the yaxis scale string</tt></dd></dl>
<dl><dt><a name="PolarAxes-grid"><strong>grid</strong></a>(self, b)</dt><dd><tt>Set the axes grids on or off; b is a boolean</tt></dd></dl>
<dl><dt><a name="PolarAxes-has_data"><strong>has_data</strong></a>(self)</dt><dd><tt>return true if any artists have been added to axes</tt></dd></dl>
<dl><dt><a name="PolarAxes-regrid"><strong>regrid</strong></a>(self, rmax)</dt></dl>
<dl><dt><a name="PolarAxes-set_rgrids"><strong>set_rgrids</strong></a>(self, radii, labels<font color="#909090">=None</font>, angle<font color="#909090">=22.5</font>, rpad<font color="#909090">=0.050000000000000003</font>, **kwargs)</dt><dd><tt>set the radial locations and labels of the r grids<br>
The labels will appear at radial distances radii at angle<br>
labels, if not None, is a len(radii) list of strings of the<br>
labels to use at each angle.<br>
if labels is None, the self.<strong>rformatter</strong> will be used<br>
rpad is a fraction of the max of radii which will pad each of<br>
the radial labels in the radial direction.<br>
<br>
Return value is a list of lines, labels where the lines are<br>
matplotlib.Line2D instances and the labels are matplotlib.Text<br>
instances<br>
kwargs control the rgrid Text label properties:<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_rmax"><strong>set_rmax</strong></a>(self, rmax)</dt></dl>
<dl><dt><a name="PolarAxes-set_thetagrids"><strong>set_thetagrids</strong></a>(self, angles, labels<font color="#909090">=None</font>, fmt<font color="#909090">='%d'</font>, frac<font color="#909090">=1.1000000000000001</font>, **kwargs)</dt><dd><tt>set the angles at which to place the theta grids (these<br>
gridlines are equal along the theta dimension). angles is in<br>
degrees<br>
labels, if not None, is a len(angles) list of strings of the<br>
labels to use at each angle.<br>
if labels is None, the labels with be fmt%angle<br>
frac is the fraction of the polar axes radius at which to<br>
place the label (1 is the edge).Eg 1.05 isd outside the axes<br>
and 0.95 is inside the axes<br>
Return value is a list of lines, labels where the lines are<br>
matplotlib.Line2D instances and the labels are matplotlib.Text<br>
instances:<br>
kwargs are optional text properties for the labels<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_xlabel"><strong>set_xlabel</strong></a>(self, xlabel, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>xlabel not implemented</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_xlim"><strong>set_xlim</strong></a>(self, xmin<font color="#909090">=None</font>, xmax<font color="#909090">=None</font>, emit<font color="#909090">=True</font>)</dt><dd><tt>set the xlimits<br>
ACCEPTS: len(2) sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_ylabel"><strong>set_ylabel</strong></a>(self, ylabel, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>ylabel not implemented</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_ylim"><strong>set_ylim</strong></a>(self, ymin<font color="#909090">=None</font>, ymax<font color="#909090">=None</font>, emit<font color="#909090">=True</font>)</dt><dd><tt>set the ylimits<br>
ACCEPTS: len(2) sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarAxes-table"><strong>table</strong></a>(self, *args, **kwargs)</dt><dd><tt>TABLE(*args, **kwargs)<br>
Not implemented for polar axes</tt></dd></dl>
<dl><dt><a name="PolarAxes-toggle_log_lineary"><strong>toggle_log_lineary</strong></a>(self)</dt><dd><tt>toggle between log and linear axes ignored for polar</tt></dd></dl>
<hr>
Data and other attributes defined here:<br>
<dl><dt><strong>RESOLUTION</strong> = 100</dl>
<hr>
Methods inherited from <a href="matplotlib.axes.html#Axes">Axes</a>:<br>
<dl><dt><a name="PolarAxes-acorr"><strong>acorr</strong></a>(self, x, **kwargs)</dt><dd><tt>ACORR(x, normed=False, detrend=detrend_none, usevlines=False,<br>
maxlags=None, **kwargs)<br>
Plot the autocorrelation of x. If normed=True, normalize the<br>
data but the autocorrelation at 0-th lag. x is detrended by<br>
the detrend callable (default no normalization.<br>
data are plotted as <a href="#PolarAxes-plot">plot</a>(lags, c, **kwargs)<br>
return value is lags, c, line where lags are a length<br>
2*maxlags+1 lag vector, c is the 2*maxlags+1 auto correlation<br>
vector, and line is a Line2D instance returned by plot. The<br>
default linestyle is None and the default marker is 'o',<br>
though these can be overridden with keyword args. The cross<br>
correlation is performed with numerix cross_correlate with<br>
mode=2.<br>
If usevlines is True, <a href="#Axes">Axes</a>.vlines rather than <a href="#Axes">Axes</a>.plot is used<br>
to draw vertical lines from the origin to the acorr.<br>
Otherwise the plotstyle is determined by the kwargs, which are<br>
Line2D properties. If usevlines, the return value is lags, c,<br>
linecol, b where linecol is the LineCollection and b is the x-axis<br>
if usevlines=True, kwargs are passed onto <a href="#Axes">Axes</a>.vlines<br>
if usevlines=False, kwargs are passed onto <a href="#Axes">Axes</a>.plot<br>
maxlags is a positive integer detailing the number of lags to show.<br>
The default value of None will return all (2*len(x)-1) lags.<br>
See the respective function for documentation on valid kwargs</tt></dd></dl>
<dl><dt><a name="PolarAxes-add_artist"><strong>add_artist</strong></a>(self, a)</dt><dd><tt>Add any artist to the axes</tt></dd></dl>
<dl><dt><a name="PolarAxes-add_collection"><strong>add_collection</strong></a>(self, collection, autolim<font color="#909090">=False</font>)</dt><dd><tt>add a Collection instance to <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="PolarAxes-add_line"><strong>add_line</strong></a>(self, line)</dt><dd><tt>Add a line to the list of plot lines</tt></dd></dl>
<dl><dt><a name="PolarAxes-add_patch"><strong>add_patch</strong></a>(self, p)</dt><dd><tt>Add a patch to the list of <a href="#Axes">Axes</a> patches; the clipbox will be<br>
set to the <a href="#Axes">Axes</a> clipping box. If the transform is not set, it<br>
wil be set to self.<strong>transData</strong>.</tt></dd></dl>
<dl><dt><a name="PolarAxes-add_table"><strong>add_table</strong></a>(self, tab)</dt><dd><tt>Add a table instance to the list of axes tables</tt></dd></dl>
<dl><dt><a name="PolarAxes-annotate"><strong>annotate</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#PolarAxes-annotate">annotate</a>(self, s, xy, textloc,<br>
xycoords='data', textcoords='data',<br>
lineprops=None,<br>
markerprops=None<br>
**props)<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-apply_aspect"><strong>apply_aspect</strong></a>(self, data_ratio<font color="#909090">=None</font>)</dt><dd><tt>Use self.<strong>_aspect</strong> and self.<strong>_adjustable</strong> to modify the<br>
axes box or the view limits.<br>
The data_ratio kwarg is set to 1 for polar axes. It is<br>
used only when _adjustable is 'box'.</tt></dd></dl>
<dl><dt><a name="PolarAxes-arrow"><strong>arrow</strong></a>(self, x, y, dx, dy, **kwargs)</dt><dd><tt>Draws arrow on specified axis from (x,y) to (x+dx,y+dy).<br>
Optional kwargs control the arrow properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-axhline"><strong>axhline</strong></a>(self, y<font color="#909090">=0</font>, xmin<font color="#909090">=0</font>, xmax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXHLINE(y=0, xmin=0, xmax=1, **kwargs)<br>
Axis Horizontal Line<br>
Draw a horizontal line at y from xmin to xmax. With the default<br>
values of xmin=0 and xmax=1, this line will always span the horizontal<br>
extent of the axes, regardless of the xlim settings, even if you<br>
change them, eg with the xlim command. That is, the horizontal extent<br>
is in axes coords: 0=left, 0.5=middle, 1.0=right but the y location is<br>
in data coordinates.<br>
Return value is the Line2D instance. kwargs are the same as kwargs to<br>
plot, and can be used to control the line properties. Eg<br>
# draw a thick red hline at y=0 that spans the xrange<br>
<a href="#PolarAxes-axhline">axhline</a>(linewidth=4, color='r')<br>
# draw a default hline at y=1 that spans the xrange<br>
<a href="#PolarAxes-axhline">axhline</a>(y=1)<br>
# draw a default hline at y=.5 that spans the the middle half of<br>
# the xrange<br>
<a href="#PolarAxes-axhline">axhline</a>(y=.5, xmin=0.25, xmax=0.75)<br>
Valid kwargs are Line2D properties<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-axhspan"><strong>axhspan</strong></a>(self, ymin, ymax, xmin<font color="#909090">=0</font>, xmax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXHSPAN(ymin, ymax, xmin=0, xmax=1, **kwargs)<br>
Axis Horizontal Span. ycoords are in data units and x<br>
coords are in axes (relative 0-1) units<br>
Draw a horizontal span (regtangle) from ymin to ymax. With the<br>
default values of xmin=0 and xmax=1, this always span the xrange,<br>
regardless of the xlim settings, even if you change them, eg with the<br>
xlim command. That is, the horizontal extent is in axes coords:<br>
0=left, 0.5=middle, 1.0=right but the y location is in data<br>
coordinates.<br>
kwargs are the kwargs to Patch, eg<br>
antialiased, aa<br>
linewidth, lw<br>
edgecolor, ec<br>
facecolor, fc<br>
the terms on the right are aliases<br>
Return value is the patches.Polygon instance.<br>
#draws a gray rectangle from y=0.25-0.75 that spans the horizontal<br>
#extent of the axes<br>
<a href="#PolarAxes-axhspan">axhspan</a>(0.25, 0.75, facecolor='0.5', alpha=0.5)<br>
Valid kwargs are Polygon properties<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-axis"><strong>axis</strong></a>(self, *v, **kwargs)</dt><dd><tt>Convenience method for manipulating the x and y view limits<br>
and the aspect ratio of the plot.<br>
<br>
kwargs are passed on to set_xlim and set_ylim -- see their docstrings for details</tt></dd></dl>
<dl><dt><a name="PolarAxes-axvline"><strong>axvline</strong></a>(self, x<font color="#909090">=0</font>, ymin<font color="#909090">=0</font>, ymax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXVLINE(x=0, ymin=0, ymax=1, **kwargs)<br>
Axis Vertical Line<br>
Draw a vertical line at x from ymin to ymax. With the default values<br>
of ymin=0 and ymax=1, this line will always span the vertical extent<br>
of the axes, regardless of the xlim settings, even if you change them,<br>
eg with the xlim command. That is, the vertical extent is in axes<br>
coords: 0=bottom, 0.5=middle, 1.0=top but the x location is in data<br>
coordinates.<br>
Return value is the Line2D instance. kwargs are the same as<br>
kwargs to plot, and can be used to control the line properties. Eg<br>
# draw a thick red vline at x=0 that spans the yrange<br>
l = <a href="#PolarAxes-axvline">axvline</a>(linewidth=4, color='r')<br>
# draw a default vline at x=1 that spans the yrange<br>
l = <a href="#PolarAxes-axvline">axvline</a>(x=1)<br>
# draw a default vline at x=.5 that spans the the middle half of<br>
# the yrange<br>
<a href="#PolarAxes-axvline">axvline</a>(x=.5, ymin=0.25, ymax=0.75)<br>
Valid kwargs are Line2D properties<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-axvspan"><strong>axvspan</strong></a>(self, xmin, xmax, ymin<font color="#909090">=0</font>, ymax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXVSPAN(xmin, xmax, ymin=0, ymax=1, **kwargs)<br>
axvspan : Axis Vertical Span. xcoords are in data units and y coords<br>
are in axes (relative 0-1) units<br>
Draw a vertical span (regtangle) from xmin to xmax. With the default<br>
values of ymin=0 and ymax=1, this always span the yrange, regardless<br>
of the ylim settings, even if you change them, eg with the ylim<br>
command. That is, the vertical extent is in axes coords: 0=bottom,<br>
0.5=middle, 1.0=top but the y location is in data coordinates.<br>
kwargs are the kwargs to Patch, eg<br>
antialiased, aa<br>
linewidth, lw<br>
edgecolor, ec<br>
facecolor, fc<br>
the terms on the right are aliases<br>
return value is the patches.Polygon instance.<br>
# draw a vertical green translucent rectangle from x=1.25 to 1.55 that<br>
# spans the yrange of the axes<br>
<a href="#PolarAxes-axvspan">axvspan</a>(1.25, 1.55, facecolor='g', alpha=0.5)<br>
Valid kwargs are Polygon properties<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-bar"><strong>bar</strong></a>(self, left, height, width<font color="#909090">=0.80000000000000004</font>, bottom<font color="#909090">=None</font>, color<font color="#909090">=None</font>, edgecolor<font color="#909090">=None</font>, linewidth<font color="#909090">=None</font>, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, ecolor<font color="#909090">=None</font>, capsize<font color="#909090">=3</font>, align<font color="#909090">='edge'</font>, orientation<font color="#909090">='vertical'</font>, log<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>BAR(left, height, width=0.8, bottom=0,<br>
color=None, edgecolor=None, linewidth=None,<br>
yerr=None, xerr=None, ecolor=None, capsize=3,<br>
align='edge', orientation='vertical', log=False)<br>
Make a bar plot with rectangles bounded by<br>
left, left+width, bottom, bottom+height<br>
(left, right, bottom and top edges)<br>
left, height, width, and bottom can be either scalars or sequences<br>
Return value is a list of Rectangle patch instances<br>
left - the x coordinates of the left sides of the bars<br>
height - the heights of the bars<br>
Optional arguments:<br>
width - the widths of the bars<br>
bottom - the y coordinates of the bottom edges of the bars<br>
color - the colors of the bars<br>
edgecolor - the colors of the bar edges<br>
linewidth - width of bar edges; None means use default<br>
linewidth; 0 means don't draw edges.<br>
xerr and yerr, if not None, will be used to generate errorbars<br>
on the bar chart<br>
ecolor specifies the color of any errorbar<br>
capsize (default 3) determines the length in points of the error<br>
bar caps<br>
align = 'edge' (default) | 'center'<br>
orientation = 'vertical' | 'horizontal'<br>
log = False | True - False (default) leaves the orientation<br>
axis as-is; True sets it to log scale<br>
For vertical bars, align='edge' aligns bars by their left edges in<br>
left, while 'center' interprets these values as the x coordinates of<br>
the bar centers. For horizontal bars, 'edge' aligns bars by their<br>
bottom edges in bottom, while 'center' interprets these values as the<br>
y coordinates of the bar centers.<br>
The optional arguments color, edgecolor, linewidth, xerr, and yerr can<br>
be either scalars or sequences of length equal to the number of bars.<br>
This enables you to use bar as the basis for stacked bar charts, or<br>
candlestick plots.<br>
Optional kwargs:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-barh"><strong>barh</strong></a>(self, bottom, width, height<font color="#909090">=0.80000000000000004</font>, left<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>BARH(bottom, width, height=0.8, left=0, **kwargs)<br>
Make a horizontal bar plot with rectangles bounded by<br>
left, left+width, bottom, bottom+height<br>
(left, right, bottom and top edges)<br>
bottom, width, height, and left can be either scalars or sequences<br>
Return value is a list of Rectangle patch instances<br>
bottom - the vertical positions of the bottom edges of the bars<br>
width - the lengths of the bars<br>
Optional arguments:<br>
height - the heights (thicknesses) of the bars<br>
left - the x coordinates of the left edges of the bars<br>
color - the colors of the bars<br>
edgecolor - the colors of the bar edges<br>
linewidth - width of bar edges; None means use default<br>
linewidth; 0 means don't draw edges.<br>
xerr and yerr, if not None, will be used to generate errorbars<br>
on the bar chart<br>
ecolor specifies the color of any errorbar<br>
capsize (default 3) determines the length in points of the error<br>
bar caps<br>
align = 'edge' (default) | 'center'<br>
log = False | True - False (default) leaves the horizontal<br>
axis as-is; True sets it to log scale<br>
Setting align='edge' aligns bars by their bottom edges in bottom,<br>
while 'center' interprets these values as the y coordinates of the bar<br>
centers.<br>
The optional arguments color, edgecolor, linewidth, xerr, and yerr can<br>
be either scalars or sequences of length equal to the number of bars.<br>
This enables you to use barh as the basis for stacked bar charts, or<br>
candlestick plots.<br>
Optional kwargs:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-boxplot"><strong>boxplot</strong></a>(self, x, notch<font color="#909090">=0</font>, sym<font color="#909090">='b+'</font>, vert<font color="#909090">=1</font>, whis<font color="#909090">=1.5</font>, positions<font color="#909090">=None</font>, widths<font color="#909090">=None</font>)</dt><dd><tt><a href="#PolarAxes-boxplot">boxplot</a>(x, notch=0, sym='+', vert=1, whis=1.5,<br>
positions=None, widths=None)<br>
<br>
Make a box and whisker plot for each column of x or<br>
each vector in sequence x.<br>
The box extends from the lower to upper quartile values<br>
of the data, with a line at the median. The whiskers<br>
extend from the box to show the range of the data. Flier<br>
points are those past the end of the whiskers.<br>
<br>
notch = 0 (default) produces a rectangular box plot.<br>
notch = 1 will produce a notched box plot<br>
<br>
sym (default 'b+') is the default symbol for flier points.<br>
Enter an empty string ('') if you don't want to show fliers.<br>
<br>
vert = 1 (default) makes the boxes vertical.<br>
vert = 0 makes horizontal boxes. This seems goofy, but<br>
that's how Matlab did it.<br>
<br>
whis (default 1.5) defines the length of the whiskers as<br>
a function of the inner quartile range. They extend to the<br>
most extreme data point within ( whis*(75%-25%) ) data range.<br>
<br>
positions (default 1,2,...,n) sets the horizontal positions of<br>
the boxes. The ticks and limits are automatically set to match<br>
the positions.<br>
<br>
widths is either a scalar or a vector and sets the width of<br>
each box. The default is 0.5, or 0.15*(distance between extreme<br>
positions) if that is smaller.<br>
<br>
x is an array or a sequence of vectors.<br>
<br>
Returns a list of the lines added.</tt></dd></dl>
<dl><dt><a name="PolarAxes-broken_barh"><strong>broken_barh</strong></a>(self, xranges, yrange, **kwargs)</dt><dd><tt>A collection of horizontal bars spanning yrange with a sequence of<br>
xranges<br>
xranges : sequence of (xmin, xwidth)<br>
yrange : (ymin, ywidth)<br>
kwargs are collections.BrokenBarHCollection properties<br>
alpha: float<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
edgecolor: matplotlib color arg or sequence of rgba tuples<br>
facecolor: matplotlib color arg or sequence of rgba tuples<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number<br>
these can either be a single argument, ie facecolors='black'<br>
or a sequence of arguments for the various bars, ie<br>
facecolors='black', 'red', 'green'</tt></dd></dl>
<dl><dt><a name="PolarAxes-clabel"><strong>clabel</strong></a>(self, CS, *args, **kwargs)</dt><dd><tt><a href="#PolarAxes-clabel">clabel</a>(CS, **kwargs) - add labels to line contours in CS,<br>
where CS is a ContourSet object returned by contour.<br>
<br>
<a href="#PolarAxes-clabel">clabel</a>(CS, V, **kwargs) - only label contours listed in V<br>
<br>
keyword arguments:<br>
<br>
* fontsize = None: as described in <a href="http://matplotlib.sf.net/fonts.html">http://matplotlib.sf.net/fonts.html</a><br>
<br>
* colors = None:<br>
<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different labels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all labels<br>
will be plotted in this color<br>
<br>
- if colors == None, the color of each label matches the color<br>
of the corresponding contour<br>
<br>
* inline = True: controls whether the underlying contour is removed<br>
(inline = True) or not (False)<br>
<br>
* fmt = '%1.3f': a format string for the label</tt></dd></dl>
<dl><dt><a name="PolarAxes-clear"><strong>clear</strong></a>(self)</dt><dd><tt>clear the axes</tt></dd></dl>
<dl><dt><a name="PolarAxes-cohere"><strong>cohere</strong></a>(self, x, y, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, window<font color="#909090">=<function window_hanning at 0xb5bc7764></font>, noverlap<font color="#909090">=0</font>, **kwargs)</dt><dd><tt>COHERE(x, y, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0, **kwargs)<br>
cohere the coherence between x and y. Coherence is the normalized<br>
cross spectral density<br>
Cxy = |Pxy|^2/(Pxx*Pyy)<br>
The return value is (Cxy, f), where f are the frequencies of the<br>
coherence vector.<br>
See the PSD help for a description of the optional parameters.<br>
kwargs are applied to the lines<br>
Returns the tuple Cxy, freqs<br>
Refs: Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)<br>
kwargs control the Line2D properties of the coherence plot:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-connect"><strong>connect</strong></a>(self, s, func)</dt><dd><tt>Register observers to be notified when certain events occur. Register<br>
with callback functions with the following signatures. The function<br>
has the following signature<br>
<br>
func(ax) # where ax is the instance making the callback.<br>
<br>
The following events can be connected to:<br>
<br>
'xlim_changed','ylim_changed'<br>
<br>
The connection id is is returned - you can use this with<br>
disconnect to disconnect from the axes event</tt></dd></dl>
<dl><dt><a name="PolarAxes-contour"><strong>contour</strong></a>(self, *args, **kwargs)</dt><dd><tt>contour and contourf draw contour lines and filled contours,<br>
respectively. Except as noted, function signatures and return<br>
values are the same for both versions.<br>
<br>
contourf differs from the Matlab (TM) version in that it does not<br>
draw the polygon edges, because the contouring engine yields<br>
simply connected regions with branch cuts. To draw the edges,<br>
add line contours with calls to contour.<br>
<br>
<br>
Function signatures<br>
<br>
<a href="#PolarAxes-contour">contour</a>(Z) - make a contour plot of an array Z. The level<br>
values are chosen automatically.<br>
<br>
<a href="#PolarAxes-contour">contour</a>(X,Y,Z) - X,Y specify the (x,y) coordinates of the surface<br>
<br>
<a href="#PolarAxes-contour">contour</a>(Z,N) and <a href="#PolarAxes-contour">contour</a>(X,Y,Z,N) - contour N automatically-chosen<br>
levels.<br>
<br>
<a href="#PolarAxes-contour">contour</a>(Z,V) and <a href="#PolarAxes-contour">contour</a>(X,Y,Z,V) - draw len(V) contour lines,<br>
at the values specified in sequence V<br>
<br>
<a href="#PolarAxes-contourf">contourf</a>(..., V) - fill the (len(V)-1) regions between the<br>
values in V<br>
<br>
<a href="#PolarAxes-contour">contour</a>(Z, **kwargs) - Use keyword args to control colors, linewidth,<br>
origin, cmap ... see below<br>
<br>
X, Y, and Z must be arrays with the same dimensions.<br>
Z may be a masked array, but filled contouring may not handle<br>
internal masked regions correctly.<br>
<br>
C = <a href="#PolarAxes-contour">contour</a>(...) returns a ContourSet object.<br>
<br>
<br>
Optional keyword args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* colors = None; or one of the following:<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different levels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all levels<br>
will be plotted in this color<br>
<br>
- if colors == None, the colormap specified by cmap will be used<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
* cmap = None: a cm Colormap instance from matplotlib.cm.<br>
- if cmap == None and colors == None, a default Colormap is used.<br>
<br>
* norm = None: a matplotlib.colors.Normalize instance for<br>
scaling data values to colors.<br>
- if norm == None, and colors == None, the default<br>
linear scaling is used.<br>
<br>
* origin = None: 'upper'|'lower'|'image'|None.<br>
If 'image', the rc value for image.origin will be used.<br>
If None (default), the first value of Z will correspond<br>
to the lower left corner, location (0,0).<br>
This keyword is active only if contourf is called with<br>
one or two arguments, that is, without explicitly<br>
specifying X and Y.<br>
<br>
* extent = None: (x0,x1,y0,y1); also active only if X and Y<br>
are not specified. If origin is not None, then extent is<br>
interpreted as in imshow: it gives the outer pixel boundaries.<br>
In this case, the position of Z[0,0] is the center of the<br>
pixel, not a corner.<br>
If origin is None, then (x0,y0) is the position of Z[0,0],<br>
and (x1,y1) is the position of Z[-1,-1].<br>
<br>
* locator = None: an instance of a ticker.Locator subclass;<br>
default is MaxNLocator. It is used to determine the<br>
contour levels if they are not given explicitly via the<br>
V argument.<br>
<br>
***** New: *****<br>
* extend = 'neither', 'both', 'min', 'max'<br>
Unless this is 'neither' (default), contour levels are<br>
automatically added to one or both ends of the range so that<br>
all data are included. These added ranges are then<br>
mapped to the special colormap values which default to<br>
the ends of the colormap range, but can be set via<br>
Colormap.set_under() and Colormap.set_over() methods.<br>
To replace clip_ends=True and V = [-100, 2, 1, 0, 1, 2, 100],<br>
use extend='both' and V = [2, 1, 0, 1, 2].<br>
****************<br>
<br>
contour only:<br>
* linewidths = None: or one of these:<br>
- a number - all levels will be plotted with this linewidth,<br>
e.g. linewidths = 0.6<br>
<br>
- a tuple of numbers, e.g. linewidths = (0.4, 0.8, 1.2) different<br>
levels will be plotted with different linewidths in the order<br>
specified<br>
<br>
- if linewidths == None, the default width in lines.linewidth in<br>
matplotlibrc is used<br>
<br>
contourf only:<br>
***** Obsolete: ****<br>
* clip_ends = True<br>
If False, the limits for color scaling are set to the<br>
minimum and maximum contour levels.<br>
True (default) clips the scaling limits. Example:<br>
if the contour boundaries are V = [-100, 2, 1, 0, 1, 2, 100],<br>
then the scaling limits will be [-100, 100] if clip_ends<br>
is False, and [-3, 3] if clip_ends is True.<br>
* linewidths = None or a number; default of 0.05 works for<br>
Postscript; a value of about 0.5 seems better for Agg.<br>
* antialiased = True (default) or False; if False, there is<br>
no need to increase the linewidths for Agg, but True gives<br>
nicer color boundaries. If antialiased is True and linewidths<br>
is too small, then there may be light-colored lines at the<br>
color boundaries caused by the antialiasing.<br>
* nchunk = 0 (default) for no subdivision of the domain;<br>
specify a positive integer to divide the domain into<br>
subdomains of roughly nchunk by nchunk points. This may<br>
never actually be advantageous, so this option may be<br>
removed. Chunking introduces artifacts at the chunk<br>
boundaries unless antialiased = False, or linewidths is<br>
set to a large enough value for the particular renderer and<br>
resolution.</tt></dd></dl>
<dl><dt><a name="PolarAxes-contourf"><strong>contourf</strong></a>(self, *args, **kwargs)</dt><dd><tt>contour and contourf draw contour lines and filled contours,<br>
respectively. Except as noted, function signatures and return<br>
values are the same for both versions.<br>
<br>
contourf differs from the Matlab (TM) version in that it does not<br>
draw the polygon edges, because the contouring engine yields<br>
simply connected regions with branch cuts. To draw the edges,<br>
add line contours with calls to contour.<br>
<br>
<br>
Function signatures<br>
<br>
<a href="#PolarAxes-contour">contour</a>(Z) - make a contour plot of an array Z. The level<br>
values are chosen automatically.<br>
<br>
<a href="#PolarAxes-contour">contour</a>(X,Y,Z) - X,Y specify the (x,y) coordinates of the surface<br>
<br>
<a href="#PolarAxes-contour">contour</a>(Z,N) and <a href="#PolarAxes-contour">contour</a>(X,Y,Z,N) - contour N automatically-chosen<br>
levels.<br>
<br>
<a href="#PolarAxes-contour">contour</a>(Z,V) and <a href="#PolarAxes-contour">contour</a>(X,Y,Z,V) - draw len(V) contour lines,<br>
at the values specified in sequence V<br>
<br>
<a href="#PolarAxes-contourf">contourf</a>(..., V) - fill the (len(V)-1) regions between the<br>
values in V<br>
<br>
<a href="#PolarAxes-contour">contour</a>(Z, **kwargs) - Use keyword args to control colors, linewidth,<br>
origin, cmap ... see below<br>
<br>
X, Y, and Z must be arrays with the same dimensions.<br>
Z may be a masked array, but filled contouring may not handle<br>
internal masked regions correctly.<br>
<br>
C = <a href="#PolarAxes-contour">contour</a>(...) returns a ContourSet object.<br>
<br>
<br>
Optional keyword args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* colors = None; or one of the following:<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different levels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all levels<br>
will be plotted in this color<br>
<br>
- if colors == None, the colormap specified by cmap will be used<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
* cmap = None: a cm Colormap instance from matplotlib.cm.<br>
- if cmap == None and colors == None, a default Colormap is used.<br>
<br>
* norm = None: a matplotlib.colors.Normalize instance for<br>
scaling data values to colors.<br>
- if norm == None, and colors == None, the default<br>
linear scaling is used.<br>
<br>
* origin = None: 'upper'|'lower'|'image'|None.<br>
If 'image', the rc value for image.origin will be used.<br>
If None (default), the first value of Z will correspond<br>
to the lower left corner, location (0,0).<br>
This keyword is active only if contourf is called with<br>
one or two arguments, that is, without explicitly<br>
specifying X and Y.<br>
<br>
* extent = None: (x0,x1,y0,y1); also active only if X and Y<br>
are not specified. If origin is not None, then extent is<br>
interpreted as in imshow: it gives the outer pixel boundaries.<br>
In this case, the position of Z[0,0] is the center of the<br>
pixel, not a corner.<br>
If origin is None, then (x0,y0) is the position of Z[0,0],<br>
and (x1,y1) is the position of Z[-1,-1].<br>
<br>
* locator = None: an instance of a ticker.Locator subclass;<br>
default is MaxNLocator. It is used to determine the<br>
contour levels if they are not given explicitly via the<br>
V argument.<br>
<br>
***** New: *****<br>
* extend = 'neither', 'both', 'min', 'max'<br>
Unless this is 'neither' (default), contour levels are<br>
automatically added to one or both ends of the range so that<br>
all data are included. These added ranges are then<br>
mapped to the special colormap values which default to<br>
the ends of the colormap range, but can be set via<br>
Colormap.set_under() and Colormap.set_over() methods.<br>
To replace clip_ends=True and V = [-100, 2, 1, 0, 1, 2, 100],<br>
use extend='both' and V = [2, 1, 0, 1, 2].<br>
****************<br>
<br>
contour only:<br>
* linewidths = None: or one of these:<br>
- a number - all levels will be plotted with this linewidth,<br>
e.g. linewidths = 0.6<br>
<br>
- a tuple of numbers, e.g. linewidths = (0.4, 0.8, 1.2) different<br>
levels will be plotted with different linewidths in the order<br>
specified<br>
<br>
- if linewidths == None, the default width in lines.linewidth in<br>
matplotlibrc is used<br>
<br>
contourf only:<br>
***** Obsolete: ****<br>
* clip_ends = True<br>
If False, the limits for color scaling are set to the<br>
minimum and maximum contour levels.<br>
True (default) clips the scaling limits. Example:<br>
if the contour boundaries are V = [-100, 2, 1, 0, 1, 2, 100],<br>
then the scaling limits will be [-100, 100] if clip_ends<br>
is False, and [-3, 3] if clip_ends is True.<br>
* linewidths = None or a number; default of 0.05 works for<br>
Postscript; a value of about 0.5 seems better for Agg.<br>
* antialiased = True (default) or False; if False, there is<br>
no need to increase the linewidths for Agg, but True gives<br>
nicer color boundaries. If antialiased is True and linewidths<br>
is too small, then there may be light-colored lines at the<br>
color boundaries caused by the antialiasing.<br>
* nchunk = 0 (default) for no subdivision of the domain;<br>
specify a positive integer to divide the domain into<br>
subdomains of roughly nchunk by nchunk points. This may<br>
never actually be advantageous, so this option may be<br>
removed. Chunking introduces artifacts at the chunk<br>
boundaries unless antialiased = False, or linewidths is<br>
set to a large enough value for the particular renderer and<br>
resolution.</tt></dd></dl>
<dl><dt><a name="PolarAxes-csd"><strong>csd</strong></a>(self, x, y, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, window<font color="#909090">=<function window_hanning at 0xb5bc7764></font>, noverlap<font color="#909090">=0</font>, **kwargs)</dt><dd><tt>CSD(x, y, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0, **kwargs)<br>
The cross spectral density Pxy by Welches average periodogram method.<br>
The vectors x and y are divided into NFFT length segments. Each<br>
segment is detrended by function detrend and windowed by function<br>
window. The product of the direct FFTs of x and y are averaged over<br>
each segment to compute Pxy, with a scaling to correct for power loss<br>
due to windowing.<br>
See the PSD help for a description of the optional parameters.<br>
Returns the tuple Pxy, freqs. Pxy is the cross spectrum (complex<br>
valued), and 10*log10(|Pxy|) is plotted<br>
Refs:<br>
Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)<br>
kwargs control the Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-disconnect"><strong>disconnect</strong></a>(self, cid)</dt><dd><tt>disconnect from the <a href="#Axes">Axes</a> event.</tt></dd></dl>
<dl><dt><a name="PolarAxes-draw_artist"><strong>draw_artist</strong></a>(self, a)</dt><dd><tt>This method can only be used after an initial draw which<br>
caches the renderer. It is used to efficiently update <a href="#Axes">Axes</a><br>
data (axis ticks, labels, etc are not updated)</tt></dd></dl>
<dl><dt><a name="PolarAxes-errorbar"><strong>errorbar</strong></a>(self, x, y, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, fmt<font color="#909090">='b-'</font>, ecolor<font color="#909090">=None</font>, capsize<font color="#909090">=3</font>, barsabove<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>ERRORBAR(x, y, yerr=None, xerr=None,<br>
fmt='b-', ecolor=None, capsize=3, barsabove=False)<br>
Plot x versus y with error deltas in yerr and xerr.<br>
Vertical errorbars are plotted if yerr is not None<br>
Horizontal errorbars are plotted if xerr is not None<br>
xerr and yerr may be any of:<br>
a rank-0, Nx1 Numpy array - symmetric errorbars +/- value<br>
an N-element list or tuple - symmetric errorbars +/- value<br>
a rank-1, Nx2 Numpy array - asymmetric errorbars -column1/+column2<br>
Alternatively, x, y, xerr, and yerr can all be scalars, which<br>
plots a single error bar at x, y.<br>
fmt is the plot format symbol for y. if fmt is None, just<br>
plot the errorbars with no line symbols. This can be useful<br>
for creating a bar plot with errorbars<br>
ecolor is a matplotlib color arg which gives the color the<br>
errorbar lines; if None, use the marker color.<br>
capsize is the size of the error bar caps in points<br>
barsabove, if True, will plot the errorbars above the plot symbols<br>
- default is below<br>
kwargs are passed on to the plot command for the markers.<br>
So you can add additional key=value pairs to control the<br>
errorbar markers. For example, this code makes big red<br>
squares with thick green edges<br>
>>> x,y,yerr = rand(3,10)<br>
>>> <a href="#PolarAxes-errorbar">errorbar</a>(x, y, yerr, marker='s',<br>
mfc='red', mec='green', ms=20, mew=4)<br>
mfc, mec, ms and mew are aliases for the longer property<br>
names, markerfacecolor, markeredgecolor, markersize and<br>
markeredgewith.<br>
valid kwargs for the marker properties are<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number<br>
Return value is a length 3 tuple. The first element is the<br>
Line2D instance for the y symbol lines. The second element is<br>
a list of error bar cap lines, the third element is a list of<br>
line collections for the horizontal and vertical error ranges</tt></dd></dl>
<dl><dt><a name="PolarAxes-fill"><strong>fill</strong></a>(self, *args, **kwargs)</dt><dd><tt>FILL(*args, **kwargs)<br>
plot filled polygons. *args is a variable length argument, allowing<br>
for multiple x,y pairs with an optional color format string; see plot<br>
for details on the argument parsing. For example, all of the<br>
following are legal, assuming ax is an <a href="#Axes">Axes</a> instance:<br>
ax.<a href="#PolarAxes-fill">fill</a>(x,y) # plot polygon with vertices at x,y<br>
ax.<a href="#PolarAxes-fill">fill</a>(x,y, 'b' ) # plot polygon with vertices at x,y in blue<br>
An arbitrary number of x, y, color groups can be specified, as in<br>
ax.<a href="#PolarAxes-fill">fill</a>(x1, y1, 'g', x2, y2, 'r')<br>
Return value is a list of patches that were added<br>
The same color strings that plot supports are supported by the fill<br>
format string.<br>
kwargs control the Polygon properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-format_xdata"><strong>format_xdata</strong></a>(self, x)</dt><dd><tt>Return x string formatted. This function will use the attribute<br>
self.<strong>fmt_xdata</strong> if it is callable, else will fall back on the xaxis<br>
major formatter</tt></dd></dl>
<dl><dt><a name="PolarAxes-format_ydata"><strong>format_ydata</strong></a>(self, y)</dt><dd><tt>Return y string formatted. This function will use the attribute<br>
self.<strong>fmt_ydata</strong> if it is callable, else will fall back on the yaxis<br>
major formatter</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_adjustable"><strong>get_adjustable</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarAxes-get_anchor"><strong>get_anchor</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarAxes-get_aspect"><strong>get_aspect</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarAxes-get_autoscale_on"><strong>get_autoscale_on</strong></a>(self)</dt><dd><tt>Get whether autoscaling is applied on plot commands</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_axis_bgcolor"><strong>get_axis_bgcolor</strong></a>(self)</dt><dd><tt>Return the axis background color</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_axisbelow"><strong>get_axisbelow</strong></a>(self)</dt><dd><tt>Get whether axist below is true or not</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_child_artists"><strong>get_child_artists</strong></a>(self)</dt><dd><tt>Return a list of artists the axes contains. Deprecated</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_cursor_props"><strong>get_cursor_props</strong></a>(self)</dt><dd><tt>return the cursor props as a linewidth, color tuple where<br>
linewidth is a float and color is an RGBA tuple</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_frame"><strong>get_frame</strong></a>(self)</dt><dd><tt>Return the axes Rectangle frame</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_frame_on"><strong>get_frame_on</strong></a>(self)</dt><dd><tt>Get whether the axes rectangle patch is drawn</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_images"><strong>get_images</strong></a>(self)</dt><dd><tt>return a list of <a href="#Axes">Axes</a> images contained by the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="PolarAxes-get_legend"><strong>get_legend</strong></a>(self)</dt><dd><tt>Return the Legend instance, or None if no legend is defined</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_lines"><strong>get_lines</strong></a>(self)</dt><dd><tt>Return a list of lines contained by the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="PolarAxes-get_navigate"><strong>get_navigate</strong></a>(self)</dt><dd><tt>Get whether the axes responds to navigation commands</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_navigate_mode"><strong>get_navigate_mode</strong></a>(self)</dt><dd><tt>Get the navigation toolbar button status: 'PAN', 'ZOOM', or None</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_position"><strong>get_position</strong></a>(self, original<font color="#909090">=False</font>)</dt><dd><tt>Return the axes rectangle left, bottom, width, height</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_renderer_cache"><strong>get_renderer_cache</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarAxes-get_window_extent"><strong>get_window_extent</strong></a>(self, *args, **kwargs)</dt><dd><tt>get the axes bounding box in display space; args and kwargs are empty</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_xaxis"><strong>get_xaxis</strong></a>(self)</dt><dd><tt>Return the XAxis instance</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_xgridlines"><strong>get_xgridlines</strong></a>(self)</dt><dd><tt>Get the x grid lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_xlim"><strong>get_xlim</strong></a>(self)</dt><dd><tt>Get the x axis range [xmin, xmax]</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_xticklabels"><strong>get_xticklabels</strong></a>(self)</dt><dd><tt>Get the xtick labels as a list of Text instances</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_xticklines"><strong>get_xticklines</strong></a>(self)</dt><dd><tt>Get the xtick lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_xticks"><strong>get_xticks</strong></a>(self)</dt><dd><tt>Return the x ticks as a list of locations</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_yaxis"><strong>get_yaxis</strong></a>(self)</dt><dd><tt>Return the YAxis instance</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_ygridlines"><strong>get_ygridlines</strong></a>(self)</dt><dd><tt>Get the y grid lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_ylim"><strong>get_ylim</strong></a>(self)</dt><dd><tt>Get the y axis range [ymin, ymax]</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_yticklabels"><strong>get_yticklabels</strong></a>(self)</dt><dd><tt>Get the ytick labels as a list of Text instances</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_yticklines"><strong>get_yticklines</strong></a>(self)</dt><dd><tt>Get the ytick lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_yticks"><strong>get_yticks</strong></a>(self)</dt><dd><tt>Return the y ticks as a list of locations</tt></dd></dl>
<dl><dt><a name="PolarAxes-hist"><strong>hist</strong></a>(self, x, bins<font color="#909090">=10</font>, normed<font color="#909090">=0</font>, bottom<font color="#909090">=None</font>, align<font color="#909090">='edge'</font>, orientation<font color="#909090">='vertical'</font>, width<font color="#909090">=None</font>, log<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>HIST(x, bins=10, normed=0, bottom=None,<br>
align='edge', orientation='vertical', width=None,<br>
log=False, **kwargs)<br>
Compute the histogram of x. bins is either an integer number of<br>
bins or a sequence giving the bins. x are the data to be binned.<br>
The return values is (n, bins, patches)<br>
If normed is true, the first element of the return tuple will<br>
be the counts normalized to form a probability density, ie,<br>
n/(len(x)*dbin). In a probability density, the integral of<br>
the histogram should be one (we assume equally spaced bins);<br>
you can verify that with<br>
# trapezoidal integration of the probability density function<br>
from matplotlib.mlab import trapz<br>
pdf, bins, patches = ax.<a href="#PolarAxes-hist">hist</a>(...)<br>
print trapz(bins, pdf)<br>
align = 'edge' | 'center'. Interprets bins either as edge<br>
or center values<br>
orientation = 'horizontal' | 'vertical'. If horizontal, barh<br>
will be used and the "bottom" kwarg will be the left edges.<br>
width: the width of the bars. If None, automatically compute<br>
the width.<br>
log: if True, the histogram axis will be set to a log scale<br>
kwargs are used to update the properties of the<br>
hist Rectangles:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-hlines"><strong>hlines</strong></a>(self, y, xmin, xmax, colors<font color="#909090">='k'</font>, linestyle<font color="#909090">='solid'</font>, label<font color="#909090">=''</font>, **kwargs)</dt><dd><tt>HLINES(y, xmin, xmax, colors='k', linestyle='solid', **kwargs)<br>
plot horizontal lines at each y from xmin to xmax. xmin or xmax can<br>
be scalars or len(x) numpy arrays. If they are scalars, then the<br>
respective values are constant, else the widths of the lines are<br>
determined by xmin and xmax<br>
colors is a line collections color args, either a single color or a len(x) list of colors<br>
linestyle is one of solid|dashed|dashdot|dotted<br>
Returns the LineCollection that was added</tt></dd></dl>
<dl><dt><a name="PolarAxes-hold"><strong>hold</strong></a>(self, b<font color="#909090">=None</font>)</dt><dd><tt>HOLD(b=None)<br>
<br>
Set the hold state. If hold is None (default), toggle the<br>
hold state. Else set the hold state to boolean value b.<br>
<br>
Eg<br>
<a href="#PolarAxes-hold">hold</a>() # toggle hold<br>
<a href="#PolarAxes-hold">hold</a>(True) # hold is on<br>
<a href="#PolarAxes-hold">hold</a>(False) # hold is off<br>
<br>
<br>
When hold is True, subsequent plot commands will be added to<br>
the current axes. When hold is False, the current axes and<br>
figure will be cleared on the next plot command</tt></dd></dl>
<dl><dt><a name="PolarAxes-imshow"><strong>imshow</strong></a>(self, X, cmap<font color="#909090">=None</font>, norm<font color="#909090">=None</font>, aspect<font color="#909090">=None</font>, interpolation<font color="#909090">=None</font>, alpha<font color="#909090">=1.0</font>, vmin<font color="#909090">=None</font>, vmax<font color="#909090">=None</font>, origin<font color="#909090">=None</font>, extent<font color="#909090">=None</font>, shape<font color="#909090">=None</font>, filternorm<font color="#909090">=1</font>, filterrad<font color="#909090">=4.0</font>, imlim<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>IMSHOW(X, cmap=None, norm=None, aspect=None, interpolation=None,<br>
alpha=1.0, vmin=None, vmax=None, origin=None, extent=None)<br>
<br>
IMSHOW(X) - plot image X to current axes, resampling to scale to axes<br>
size (X may be numarray/Numeric array or PIL image)<br>
<br>
IMSHOW(X, **kwargs) - Use keyword args to control image scaling,<br>
colormapping etc. See below for details<br>
<br>
<br>
Display the image in X to current axes. X may be a float array, a<br>
UInt8 array or a PIL image. If X is an array, X can have the following<br>
shapes:<br>
<br>
MxN : luminance (grayscale, float array only)<br>
<br>
MxNx3 : RGB (float or UInt8 array)<br>
<br>
MxNx4 : RGBA (float or UInt8 array)<br>
<br>
The value for each component of MxNx3 and MxNx4 float arrays should be<br>
in the range 0.0 to 1.0; MxN float arrays may be normalised.<br>
<br>
A matplotlib.image.AxesImage instance is returned<br>
<br>
The following kwargs are allowed:<br>
<br>
* cmap is a cm colormap instance, eg cm.jet. If None, default to rc<br>
image.cmap value (Ignored when X has RGB(A) information)<br>
<br>
* aspect is one of: auto, equal, or a number. If None, default to rc<br>
image.aspect value<br>
<br>
* interpolation is one of:<br>
<br>
'nearest', 'bilinear', 'bicubic', 'spline16', 'spline36',<br>
'hanning', 'hamming', 'hermite', 'kaiser', 'quadric',<br>
'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc',<br>
'lanczos', 'blackman'<br>
<br>
if interpolation is None, default to rc<br>
image.interpolation. See also th the filternorm and<br>
filterrad parameters<br>
<br>
* norm is a matplotlib.colors.Normalize instance; default is<br>
normalization(). This scales luminance -> 0-1 (only used for an<br>
MxN float array).<br>
<br>
* vmin and vmax are used to scale a luminance image to 0-1. If<br>
either is None, the min and max of the luminance values will be<br>
used. Note if you pass a norm instance, the settings for vmin and<br>
vmax will be ignored.<br>
<br>
* alpha = 1.0 : the alpha blending value<br>
<br>
* origin is 'upper' or 'lower', to place the [0,0]<br>
index of the array in the upper left or lower left corner of<br>
the axes. If None, default to rc image.origin<br>
<br>
* extent is (left, right, bottom, top) data values of the<br>
axes. The default assigns zero-based row, column indices<br>
to the x, y centers of the pixels.<br>
<br>
* shape is for raw buffer images<br>
<br>
* filternorm is a parameter for the antigrain image resize<br>
filter. From the antigrain documentation, if normalize=1,<br>
the filter normalizes integer values and corrects the<br>
rounding errors. It doesn't do anything with the source<br>
floating point values, it corrects only integers according<br>
to the rule of 1.0 which means that any sum of pixel<br>
weights must be equal to 1.0. So, the filter function<br>
must produce a graph of the proper shape.<br>
<br>
* filterrad: the filter radius for filters that have a radius<br>
parameter, ie when interpolation is one of: 'sinc',<br>
'lanczos' or 'blackman'<br>
<br>
Additional kwargs are matplotlib.artist properties</tt></dd></dl>
<dl><dt><a name="PolarAxes-in_axes"><strong>in_axes</strong></a>(self, xwin, ywin)</dt><dd><tt>return True is the point xwin, ywin (display coords) are in the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="PolarAxes-ishold"><strong>ishold</strong></a>(self)</dt><dd><tt>return the HOLD status of the axes</tt></dd></dl>
<dl><dt><a name="PolarAxes-legend"><strong>legend</strong></a>(self, *args, **kwargs)</dt><dd><tt>LEGEND(*args, **kwargs)<br>
<br>
Place a legend on the current axes at location loc. Labels are a<br>
sequence of strings and loc can be a string or an integer specifying<br>
the legend location<br>
<br>
USAGE:<br>
<br>
Make a legend with existing lines<br>
<br>
>>> <a href="#PolarAxes-legend">legend</a>()<br>
<br>
legend by itself will try and build a legend using the label<br>
property of the lines/patches/collections. You can set the label of<br>
a line by doing <a href="#PolarAxes-plot">plot</a>(x, y, label='my data') or line.<a href="#PolarAxes-set_label">set_label</a>('my<br>
data'). If label is set to '_nolegend_', the item will not be shown<br>
in legend.<br>
<br>
# automatically generate the legend from labels<br>
<a href="#PolarAxes-legend">legend</a>( ('label1', 'label2', 'label3') )<br>
<br>
# Make a legend for a list of lines and labels<br>
<a href="#PolarAxes-legend">legend</a>( (line1, line2, line3), ('label1', 'label2', 'label3') )<br>
<br>
# Make a legend at a given location, using a location argument<br>
# <a href="#PolarAxes-legend">legend</a>( LABELS, LOC ) or<br>
# <a href="#PolarAxes-legend">legend</a>( LINES, LABELS, LOC )<br>
<a href="#PolarAxes-legend">legend</a>( ('label1', 'label2', 'label3'), loc='upper left')<br>
<a href="#PolarAxes-legend">legend</a>( (line1, line2, line3), ('label1', 'label2', 'label3'), loc=2)<br>
<br>
The location codes are<br>
<br>
'best' : 0,<br>
'upper right' : 1, (default)<br>
'upper left' : 2,<br>
'lower left' : 3,<br>
'lower right' : 4,<br>
'right' : 5,<br>
'center left' : 6,<br>
'center right' : 7,<br>
'lower center' : 8,<br>
'upper center' : 9,<br>
'center' : 10,<br>
<br>
If none of these are suitable, loc can be a 2-tuple giving x,y<br>
in axes coords, ie,<br>
<br>
loc = 0, 1 is left top<br>
loc = 0.5, 0.5 is center, center<br>
<br>
and so on. The following kwargs are supported:<br>
<br>
isaxes=True # whether this is an axes legend<br>
numpoints = 4 # the number of points in the legend line<br>
prop = FontProperties(size='smaller') # the font property<br>
pad = 0.2 # the fractional whitespace inside the legend border<br>
markerscale = 0.6 # the relative size of legend markers vs. original<br>
shadow # if True, draw a shadow behind legend<br>
labelsep = 0.005 # the vertical space between the legend entries<br>
handlelen = 0.05 # the length of the legend lines<br>
handletextsep = 0.02 # the space between the legend line and legend text<br>
axespad = 0.02 # the border between the axes and legend edge</tt></dd></dl>
<dl><dt><a name="PolarAxes-loglog"><strong>loglog</strong></a>(self, *args, **kwargs)</dt><dd><tt>LOGLOG(*args, **kwargs)<br>
Make a loglog plot with log scaling on the a and y axis. The args<br>
to semilog x are the same as the args to plot. See help plot for<br>
more info.<br>
Optional keyword args supported are any of the kwargs<br>
supported by plot or set_xscale or set_yscale. Notable, for<br>
log scaling:<br>
* basex: base of the x logarithm<br>
* subsx: the location of the minor ticks; None defaults to<br>
autosubs, which depend on the number of decades in the<br>
plot; see set_xscale for details<br>
* basey: base of the y logarithm<br>
* subsy: the location of the minor yticks; None defaults to<br>
autosubs, which depend on the number of decades in the<br>
plot; see set_yscale for details<br>
The remaining valid kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-matshow"><strong>matshow</strong></a>(self, Z, **kwargs)</dt><dd><tt>Plot a matrix as an image.<br>
<br>
The matrix will be shown the way it would be printed,<br>
with the first row at the top. Row and column numbering<br>
is zero-based.<br>
<br>
Argument:<br>
Z anything that can be interpreted as a 2-D array<br>
<br>
kwargs: all are passed to imshow. matshow sets defaults<br>
for extent, origin, interpolation, and aspect; use care<br>
in overriding the extent and origin kwargs, because they<br>
interact. (Also, if you want to change them, you probably<br>
should be using imshow directly in your own version of<br>
matshow.)<br>
<br>
Returns: an AxesImage instance</tt></dd></dl>
<dl><dt><a name="PolarAxes-panx"><strong>panx</strong></a>(self, numsteps)</dt><dd><tt>Pan the x axis numsteps (plus pan right, minus pan left)</tt></dd></dl>
<dl><dt><a name="PolarAxes-pany"><strong>pany</strong></a>(self, numsteps)</dt><dd><tt>Pan the x axis numsteps (plus pan up, minus pan down)</tt></dd></dl>
<dl><dt><a name="PolarAxes-pcolor"><strong>pcolor</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#PolarAxes-pcolor">pcolor</a>(*args, **kwargs): pseudocolor plot of a 2-D array<br>
Function signatures<br>
<a href="#PolarAxes-pcolor">pcolor</a>(C, **kwargs)<br>
<a href="#PolarAxes-pcolor">pcolor</a>(X, Y, C, **kwargs)<br>
C is the array of color values<br>
X and Y, if given, specify the (x,y) coordinates of the colored<br>
quadrilaterals; the quadrilateral for C[i,j] has corners at<br>
(X[i,j],Y[i,j]), (X[i,j+1],Y[i,j+1]), (X[i+1,j],Y[i+1,j]),<br>
(X[i+1,j+1],Y[i+1,j+1]). Ideally the dimensions of X and Y<br>
should be one greater than those of C; if the dimensions are the<br>
same, then the last row and column of C will be ignored.<br>
Note that the the column index corresponds to the x-coordinate,<br>
and the row index corresponds to y; for details, see<br>
the "Grid Orientation" section below.<br>
If either or both of X and Y are 1-D arrays or column vectors,<br>
they will be expanded as needed into the appropriate 2-D arrays,<br>
making a rectangular grid.<br>
X,Y and C may be masked arrays. If either C[i,j], or one<br>
of the vertices surrounding C[i,j] (X or Y at [i,j],[i+1,j],<br>
[i,j+1],[i=1,j+1]) is masked, nothing is plotted.<br>
Optional keyword args are shown with their defaults below (you must<br>
use kwargs for these):<br>
* cmap = cm.jet : a cm Colormap instance from matplotlib.cm.<br>
defaults to cm.jet<br>
* norm = Normalize() : matplotlib.colors.Normalize instance<br>
is used to scale luminance data to 0,1.<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used. If you pass a norm<br>
instance, vmin and vmax will be None<br>
* shading = 'flat' : or 'faceted'. If 'faceted', a black grid is<br>
drawn around each rectangle; if 'flat', edges are not drawn<br>
* alpha=1.0 : the alpha blending value<br>
Return value is a matplotlib.collections.PatchCollection<br>
object<br>
Grid Orientation<br>
The orientation follows the Matlab(TM) convention: an<br>
array C with shape (nrows, ncolumns) is plotted with<br>
the column number as X and the row number as Y, increasing<br>
up; hence it is plotted the way the array would be printed,<br>
except that the Y axis is reversed. That is, C is taken<br>
as C(y,x).<br>
Similarly for meshgrid:<br>
x = arange(5)<br>
y = arange(3)<br>
X, Y = meshgrid(x,y)<br>
is equivalent to<br>
X = array([[0, 1, 2, 3, 4],<br>
[0, 1, 2, 3, 4],<br>
[0, 1, 2, 3, 4]])<br>
Y = array([[0, 0, 0, 0, 0],<br>
[1, 1, 1, 1, 1],<br>
[2, 2, 2, 2, 2]])<br>
so if you have<br>
C = rand( len(x), len(y))<br>
then you need<br>
<a href="#PolarAxes-pcolor">pcolor</a>(X, Y, transpose(C))<br>
or<br>
<a href="#PolarAxes-pcolor">pcolor</a>(transpose(C))<br>
Dimensions<br>
Matlab pcolor always discards<br>
the last row and column of C, but matplotlib displays<br>
the last row and column if X and Y are not specified, or<br>
if X and Y have one more row and column than C.<br>
kwargs can be used to control the PolyCollection properties:<br>
alpha: float<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
edgecolor: matplotlib color arg or sequence of rgba tuples<br>
facecolor: matplotlib color arg or sequence of rgba tuples<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-pcolor_classic"><strong>pcolor_classic</strong></a>(self, *args)</dt><dd><tt>pcolor_classic is no longer available; please use pcolor,<br>
which is a drop-in replacement.</tt></dd></dl>
<dl><dt><a name="PolarAxes-pcolormesh"><strong>pcolormesh</strong></a>(self, *args, **kwargs)</dt><dd><tt>PCOLORMESH(*args, **kwargs)<br>
Function signatures<br>
PCOLORMESH(C) - make a pseudocolor plot of matrix C<br>
PCOLORMESH(X, Y, C) - a pseudo color plot of C on the matrices X and Y<br>
PCOLORMESH(C, **kwargs) - Use keyword args to control colormapping and<br>
scaling; see below<br>
C may be a masked array, but X and Y may not. Masked array support<br>
is implemented via cmap and norm; in contrast, pcolor simply does<br>
not draw quadrilaterals with masked colors or vertices.<br>
Optional keyword args are shown with their defaults below (you must<br>
use kwargs for these):<br>
* cmap = cm.jet : a cm Colormap instance from matplotlib.cm.<br>
defaults to cm.jet<br>
* norm = Normalize() : matplotlib.colors.Normalize instance<br>
is used to scale luminance data to 0,1. Instantiate it<br>
with clip=False if C is a masked array.<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used.<br>
* shading = 'flat' : or 'faceted'. If 'faceted', a black grid is<br>
drawn around each rectangle; if 'flat', edge colors are same as<br>
face colors<br>
* alpha=1.0 : the alpha blending value<br>
Return value is a matplotlib.collections.PatchCollection<br>
object<br>
See pcolor for an explantion of the grid orientation and the<br>
expansion of 1-D X and/or Y to 2-D arrays.<br>
kwargs can be used to control the QuadMesh polygon collection properties:<br>
alpha: float<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
edgecolor: matplotlib color arg or sequence of rgba tuples<br>
facecolor: matplotlib color arg or sequence of rgba tuples<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-pick"><strong>pick</strong></a>(self, *args)</dt><dd><tt><a href="#PolarAxes-pick">pick</a>(mouseevent)<br>
<br>
each child artist will fire a pick event if mouseevent is over<br>
the artist and the artist has picker set</tt></dd></dl>
<dl><dt><a name="PolarAxes-pie"><strong>pie</strong></a>(self, x, explode<font color="#909090">=None</font>, labels<font color="#909090">=None</font>, colors<font color="#909090">=None</font>, autopct<font color="#909090">=None</font>, pctdistance<font color="#909090">=0.59999999999999998</font>, shadow<font color="#909090">=False</font>)</dt><dd><tt>PIE(x, explode=None, labels=None,<br>
colors=('b', 'g', 'r', 'c', 'm', 'y', 'k', 'w'),<br>
autopct=None, pctdistance=0.6, shadow=False)<br>
<br>
Make a pie chart of array x. The fractional area of each wedge is<br>
given by x/sum(x). If sum(x)<=1, then the values of x give the<br>
fractional area directly and the array will not be normalized.<br>
<br>
- explode, if not None, is a len(x) array which specifies the<br>
fraction of the radius to offset that wedge.<br>
<br>
- colors is a sequence of matplotlib color args that the pie chart<br>
will cycle.<br>
<br>
- labels, if not None, is a len(x) list of labels.<br>
<br>
- autopct, if not None, is a string or function used to label the<br>
wedges with their numeric value. The label will be placed inside<br>
the wedge. If it is a format string, the label will be fmt%pct.<br>
If it is a function, it will be called<br>
<br>
- pctdistance is the ratio between the center of each pie slice<br>
and the start of the text generated by autopct. Ignored if autopct<br>
is None; default is 0.6.<br>
<br>
- shadow, if True, will draw a shadow beneath the pie.<br>
<br>
The pie chart will probably look best if the figure and axes are<br>
square. Eg,<br>
<br>
figure(figsize=(8,8))<br>
ax = axes([0.1, 0.1, 0.8, 0.8])<br>
<br>
Return value:<br>
<br>
If autopct is None, return a list of (patches, texts), where patches<br>
is a sequence of matplotlib.patches.Wedge instances and texts is a<br>
list of the label Text instnaces<br>
<br>
If autopct is not None, return (patches, texts, autotexts), where<br>
patches and texts are as above, and autotexts is a list of text<br>
instances for the numeric labels</tt></dd></dl>
<dl><dt><a name="PolarAxes-plot"><strong>plot</strong></a>(self, *args, **kwargs)</dt><dd><tt>PLOT(*args, **kwargs)<br>
Plot lines and/or markers to the <a href="#Axes">Axes</a>. *args is a variable length<br>
argument, allowing for multiple x,y pairs with an optional format<br>
string. For example, each of the following is legal<br>
<a href="#PolarAxes-plot">plot</a>(x,y) # plot x and y using the default line style and color<br>
<a href="#PolarAxes-plot">plot</a>(x,y, 'bo') # plot x and y using blue circle markers<br>
<a href="#PolarAxes-plot">plot</a>(y) # plot y using x as index array 0..N-1<br>
<a href="#PolarAxes-plot">plot</a>(y, 'r+') # ditto, but with red plusses<br>
If x and/or y is 2-Dimensional, then the corresponding columns<br>
will be plotted.<br>
An arbitrary number of x, y, fmt groups can be specified, as in<br>
a.<a href="#PolarAxes-plot">plot</a>(x1, y1, 'g^', x2, y2, 'g-')<br>
Return value is a list of lines that were added.<br>
The following line styles are supported:<br>
- : solid line<br>
-- : dashed line<br>
-. : dash-dot line<br>
: : dotted line<br>
. : points<br>
, : pixels<br>
o : circle symbols<br>
^ : triangle up symbols<br>
v : triangle down symbols<br>
< : triangle left symbols<br>
> : triangle right symbols<br>
s : square symbols<br>
+ : plus symbols<br>
x : cross symbols<br>
D : diamond symbols<br>
d : thin diamond symbols<br>
1 : tripod down symbols<br>
2 : tripod up symbols<br>
3 : tripod left symbols<br>
4 : tripod right symbols<br>
h : hexagon symbols<br>
H : rotated hexagon symbols<br>
p : pentagon symbols<br>
| : vertical line symbols<br>
_ : horizontal line symbols<br>
steps : use gnuplot style 'steps' # kwarg only<br>
The following color abbreviations are supported<br>
b : blue<br>
g : green<br>
r : red<br>
c : cyan<br>
m : magenta<br>
y : yellow<br>
k : black<br>
w : white<br>
In addition, you can specify colors in many weird and<br>
wonderful ways, including full names 'green', hex strings<br>
'#008000', RGB or RGBA tuples (0,1,0,1) or grayscale<br>
intensities as a string '0.8'.<br>
Line styles and colors are combined in a single format string, as in<br>
'bo' for blue circles.<br>
The **kwargs can be used to set line properties (any property that has<br>
a set_* method). You can use this to set a line label (for auto<br>
legends), linewidth, anitialising, marker face color, etc. Here is an<br>
example:<br>
<a href="#PolarAxes-plot">plot</a>([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2)<br>
<a href="#PolarAxes-plot">plot</a>([1,2,3], [1,4,9], 'rs', label='line 2')<br>
<a href="#PolarAxes-axis">axis</a>([0, 4, 0, 10])<br>
<a href="#PolarAxes-legend">legend</a>()<br>
If you make multiple lines with one plot command, the kwargs apply<br>
to all those lines, eg<br>
<a href="#PolarAxes-plot">plot</a>(x1, y1, x2, y2, antialised=False)<br>
Neither line will be antialiased.<br>
The kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number<br>
kwargs scalex and scaley, if defined, are passed on<br>
to autoscale_view to determine whether the x and y axes are<br>
autoscaled; default True. See <a href="#Axes">Axes</a>.autoscale_view for more<br>
information</tt></dd></dl>
<dl><dt><a name="PolarAxes-plot_date"><strong>plot_date</strong></a>(self, x, y, fmt<font color="#909090">='bo'</font>, tz<font color="#909090">=None</font>, xdate<font color="#909090">=True</font>, ydate<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>PLOT_DATE(x, y, fmt='bo', tz=None, xdate=True, ydate=False, **kwargs)<br>
Similar to the <a href="#PolarAxes-plot">plot</a>() command, except the x or y (or both) data<br>
is considered to be dates, and the axis is labeled accordingly.<br>
x or y (or both) can be a sequence of dates represented as<br>
float days since 0001-01-01 UTC.<br>
fmt is a plot format string.<br>
tz is the time zone to use in labelling dates. Defaults to rc value.<br>
If xdate is True, the x-axis will be labeled with dates.<br>
If ydate is True, the y-axis will be labeled with dates.<br>
Note if you are using custom date tickers and formatters, it<br>
may be necessary to set the formatters/locators after the call<br>
to plot_date since plot_date will set the default tick locator<br>
to AutoDateLocator (if the tick locator is not already set to<br>
a DateLocator instance) and the default tick formatter to<br>
AutoDateFormatter (if the tick formatter is not already set to<br>
a DateFormatter instance).<br>
Valid kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number<br>
See matplotlib.dates for helper functions date2num, num2date<br>
and drange for help on creating the required floating point dates</tt></dd></dl>
<dl><dt><a name="PolarAxes-psd"><strong>psd</strong></a>(self, x, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, window<font color="#909090">=<function window_hanning at 0xb5bc7764></font>, noverlap<font color="#909090">=0</font>, **kwargs)</dt><dd><tt>PSD(x, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0, **kwargs)<br>
The power spectral density by Welches average periodogram method. The<br>
vector x is divided into NFFT length segments. Each segment is<br>
detrended by function detrend and windowed by function window.<br>
noperlap gives the length of the overlap between segments. The<br>
absolute(fft(segment))**2 of each segment are averaged to compute Pxx,<br>
with a scaling to correct for power loss due to windowing. Fs is the<br>
sampling frequency.<br>
NFFT is the length of the fft segment; must be a power of 2<br>
Fs is the sampling frequency.<br>
detrend - the function applied to each segment before fft-ing,<br>
designed to remove the mean or linear trend. Unlike in matlab,<br>
where the detrend parameter is a vector, in matplotlib is it a<br>
function. The mlab module defines detrend_none, detrend_mean,<br>
detrend_linear, but you can use a custom function as well.<br>
window - the function used to window the segments. window is a<br>
function, unlike in matlab(TM) where it is a vector. mlab defines<br>
window_none, window_hanning, but you can use a custom function<br>
as well.<br>
noverlap gives the length of the overlap between segments.<br>
Returns the tuple Pxx, freqs<br>
For plotting, the power is plotted as 10*log10(pxx)) for decibels,<br>
though pxx itself is returned<br>
Refs:<br>
Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)<br>
kwargs control the Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-quiver"><strong>quiver</strong></a>(self, *args, **kw)</dt><dd><tt>Plot a 2-D field of arrows.<br>
<br>
Function signatures:<br>
<br>
<a href="#PolarAxes-quiver">quiver</a>(U, V, **kw)<br>
<a href="#PolarAxes-quiver">quiver</a>(U, V, C, **kw)<br>
<a href="#PolarAxes-quiver">quiver</a>(X, Y, U, V, **kw)<br>
<a href="#PolarAxes-quiver">quiver</a>(X, Y, U, V, C, **kw)<br>
<br>
Arguments:<br>
<br>
X, Y give the x and y coordinates of the arrow locations<br>
(default is tail of arrow; see 'pivot' kwarg)<br>
U, V give the x and y components of the arrow vectors<br>
C is an optional array used to map colors to the arrows<br>
<br>
All arguments may be 1-D or 2-D arrays or sequences.<br>
If X and Y are absent, they will be generated as a uniform grid.<br>
If U and V are 2-D arrays but X and Y are 1-D, and if<br>
len(X) and len(Y) match the column and row dimensions<br>
of U, then X and Y will be expanded with meshgrid.<br>
<br>
Keyword arguments (default given first):<br>
<br>
* units = 'width' | 'height' | 'dots' | 'inches' | 'x' | 'y'<br>
arrow units; the arrow dimensions *except for length*<br>
are in multiples of this unit.<br>
* scale = None | float<br>
data units per arrow unit, e.g. m/s per plot width;<br>
a smaller scale parameter makes the arrow longer.<br>
If None, a simple autoscaling algorithm is used, based<br>
on the average vector length and the number of vectors.<br>
<br>
Arrow dimensions and scales can be in any of several units:<br>
<br>
'width' or 'height': the width or height of the axes<br>
'dots' or 'inches': pixels or inches, based on the figure dpi<br>
'x' or 'y': X or Y data units<br>
<br>
In all cases the arrow aspect ratio is 1, so that if U==V the angle<br>
of the arrow on the plot is 45 degrees CCW from the X-axis.<br>
<br>
The arrows scale differently depending on the units, however.<br>
For 'x' or 'y', the arrows get larger as one zooms in; for other<br>
units, the arrow size is independent of the zoom state. For<br>
'width or 'height', the arrow size increases with the width and<br>
height of the axes, respectively, when the the window is resized;<br>
for 'dots' or 'inches', resizing does not change the arrows.<br>
<br>
<br>
* width = ? shaft width in arrow units; default depends on<br>
choice of units, above, and number of vectors;<br>
a typical starting value is about<br>
0.005 times the width of the plot.<br>
* headwidth = 3 head width as multiple of shaft width<br>
* headlength = 5 head length as multiple of shaft width<br>
* headaxislength = 4.5 head length at shaft intersection<br>
* minshaft = 1 length below which arrow scales, in units<br>
of head length. Do not set this to less<br>
than 1, or small arrows will look terrible!<br>
* minlength = 1 minimum length as a multiple of shaft width;<br>
if an arrow length is less than this, plot a<br>
dot (hexagon) of this diameter instead.<br>
<br>
The defaults give a slightly swept-back arrow; to make the<br>
head a triangle, make headaxislength the same as headlength.<br>
To make the arrow more pointed, reduce headwidth or increase<br>
headlength and headaxislength.<br>
To make the head smaller relative to the shaft, scale down<br>
all the head* parameters.<br>
You will probably do best to leave minshaft alone.<br>
<br>
* pivot = 'tail' | 'middle' | 'tip'<br>
The part of the arrow that is at the grid point; the arrow<br>
rotates about this point, hence the name 'pivot'.<br>
<br>
* color = 'k' | any matplotlib color spec or sequence of color specs.<br>
This is a synonym for the PolyCollection facecolor kwarg.<br>
If C has been set, 'color' has no effect.<br>
<br>
* All PolyCollection kwargs are valid, in the sense that they<br>
will be passed on to the PolyCollection constructor.<br>
In particular, one might want to use, for example:<br>
linewidths = (1,), edgecolors = ('g',)<br>
to make the arrows have green outlines of unit width.</tt></dd></dl>
<dl><dt><a name="PolarAxes-quiver2"><strong>quiver2</strong></a>(self, *args, **kw)</dt><dd><tt>Plot a 2-D field of arrows.<br>
<br>
Function signatures:<br>
<br>
<a href="#PolarAxes-quiver">quiver</a>(U, V, **kw)<br>
<a href="#PolarAxes-quiver">quiver</a>(U, V, C, **kw)<br>
<a href="#PolarAxes-quiver">quiver</a>(X, Y, U, V, **kw)<br>
<a href="#PolarAxes-quiver">quiver</a>(X, Y, U, V, C, **kw)<br>
<br>
Arguments:<br>
<br>
X, Y give the x and y coordinates of the arrow locations<br>
(default is tail of arrow; see 'pivot' kwarg)<br>
U, V give the x and y components of the arrow vectors<br>
C is an optional array used to map colors to the arrows<br>
<br>
All arguments may be 1-D or 2-D arrays or sequences.<br>
If X and Y are absent, they will be generated as a uniform grid.<br>
If U and V are 2-D arrays but X and Y are 1-D, and if<br>
len(X) and len(Y) match the column and row dimensions<br>
of U, then X and Y will be expanded with meshgrid.<br>
<br>
Keyword arguments (default given first):<br>
<br>
* units = 'width' | 'height' | 'dots' | 'inches' | 'x' | 'y'<br>
arrow units; the arrow dimensions *except for length*<br>
are in multiples of this unit.<br>
* scale = None | float<br>
data units per arrow unit, e.g. m/s per plot width;<br>
a smaller scale parameter makes the arrow longer.<br>
If None, a simple autoscaling algorithm is used, based<br>
on the average vector length and the number of vectors.<br>
<br>
Arrow dimensions and scales can be in any of several units:<br>
<br>
'width' or 'height': the width or height of the axes<br>
'dots' or 'inches': pixels or inches, based on the figure dpi<br>
'x' or 'y': X or Y data units<br>
<br>
In all cases the arrow aspect ratio is 1, so that if U==V the angle<br>
of the arrow on the plot is 45 degrees CCW from the X-axis.<br>
<br>
The arrows scale differently depending on the units, however.<br>
For 'x' or 'y', the arrows get larger as one zooms in; for other<br>
units, the arrow size is independent of the zoom state. For<br>
'width or 'height', the arrow size increases with the width and<br>
height of the axes, respectively, when the the window is resized;<br>
for 'dots' or 'inches', resizing does not change the arrows.<br>
<br>
<br>
* width = ? shaft width in arrow units; default depends on<br>
choice of units, above, and number of vectors;<br>
a typical starting value is about<br>
0.005 times the width of the plot.<br>
* headwidth = 3 head width as multiple of shaft width<br>
* headlength = 5 head length as multiple of shaft width<br>
* headaxislength = 4.5 head length at shaft intersection<br>
* minshaft = 1 length below which arrow scales, in units<br>
of head length. Do not set this to less<br>
than 1, or small arrows will look terrible!<br>
* minlength = 1 minimum length as a multiple of shaft width;<br>
if an arrow length is less than this, plot a<br>
dot (hexagon) of this diameter instead.<br>
<br>
The defaults give a slightly swept-back arrow; to make the<br>
head a triangle, make headaxislength the same as headlength.<br>
To make the arrow more pointed, reduce headwidth or increase<br>
headlength and headaxislength.<br>
To make the head smaller relative to the shaft, scale down<br>
all the head* parameters.<br>
You will probably do best to leave minshaft alone.<br>
<br>
* pivot = 'tail' | 'middle' | 'tip'<br>
The part of the arrow that is at the grid point; the arrow<br>
rotates about this point, hence the name 'pivot'.<br>
<br>
* color = 'k' | any matplotlib color spec or sequence of color specs.<br>
This is a synonym for the PolyCollection facecolor kwarg.<br>
If C has been set, 'color' has no effect.<br>
<br>
* All PolyCollection kwargs are valid, in the sense that they<br>
will be passed on to the PolyCollection constructor.<br>
In particular, one might want to use, for example:<br>
linewidths = (1,), edgecolors = ('g',)<br>
to make the arrows have green outlines of unit width.</tt></dd></dl>
<dl><dt><a name="PolarAxes-quiver_classic"><strong>quiver_classic</strong></a>(self, U, V, *args, **kwargs)</dt><dd><tt>QUIVER( X, Y, U, V )<br>
QUIVER( U, V )<br>
QUIVER( X, Y, U, V, S)<br>
QUIVER( U, V, S )<br>
QUIVER( ..., color=None, width=1.0, cmap=None, norm=None )<br>
<br>
Make a vector plot (U, V) with arrows on a grid (X, Y)<br>
<br>
If X and Y are not specified, U and V must be 2D arrays. Equally spaced<br>
X and Y grids are then generated using the meshgrid command.<br>
<br>
color can be a color value or an array of colors, so that the arrows can be<br>
colored according to another dataset. If cmap is specified and color is 'length',<br>
the colormap is used to give a color according to the vector's length.<br>
<br>
If color is a scalar field, the colormap is used to map the scalar to a color<br>
If a colormap is specified and color is an array of color triplets, then the<br>
colormap is ignored<br>
<br>
width is a scalar that controls the width of the arrows<br>
<br>
if S is specified it is used to scale the vectors. Use S=0 to disable automatic<br>
scaling.<br>
If S!=0, vectors are scaled to fit within the grid and then are multiplied by S.</tt></dd></dl>
<dl><dt><a name="PolarAxes-quiverkey"><strong>quiverkey</strong></a>(self, *args, **kw)</dt><dd><tt>Add a key to a quiver plot.<br>
<br>
Function signature:<br>
<a href="#PolarAxes-quiverkey">quiverkey</a>(Q, X, Y, U, label, **kw)<br>
<br>
Arguments:<br>
Q is the Quiver instance returned by a call to quiver.<br>
X, Y give the location of the key; additional explanation follows.<br>
U is the length of the key<br>
label is a string with the length and units of the key<br>
<br>
Keyword arguments (default given first):<br>
* coordinates = 'axes' | 'figure' | 'data' | 'inches'<br>
Coordinate system and units for X, Y: 'axes' and 'figure'<br>
are normalized coordinate systems with 0,0 in the lower<br>
left and 1,1 in the upper right; 'data' are the axes<br>
data coordinates (used for the locations of the vectors<br>
in the quiver plot itself); 'inches' is position in the<br>
figure in inches, with 0,0 at the lower left corner.<br>
* color overrides face and edge colors from Q.<br>
* labelpos = 'N' | 'S' | 'E' | 'W'<br>
Position the label above, below, to the right, to the left<br>
of the arrow, respectively.<br>
* labelsep = 0.1 inches distance between the arrow and the label<br>
* labelcolor (defaults to default Text color)<br>
* fontproperties is a dictionary with keyword arguments accepted<br>
by the FontProperties initializer: family, style, variant,<br>
size, weight<br>
<br>
Any additional keyword arguments are used to override vector<br>
properties taken from Q.<br>
<br>
The positioning of the key depends on X, Y, coordinates, and<br>
labelpos. If labelpos is 'N' or 'S', X,Y give the position<br>
of the middle of the key arrow. If labelpos is 'E', X,Y<br>
positions the head, and if labelpos is 'W', X,Y positions the<br>
tail; in either of these two cases, X,Y is somewhere in the middle<br>
of the arrow+label key object.</tt></dd></dl>
<dl><dt><a name="PolarAxes-redraw_in_frame"><strong>redraw_in_frame</strong></a>(self)</dt><dd><tt>This method can only be used after an initial draw which<br>
caches the renderer. It is used to efficiently update <a href="#Axes">Axes</a><br>
data (axis ticks, labels, etc are not updated)</tt></dd></dl>
<dl><dt><a name="PolarAxes-relim"><strong>relim</strong></a>(self)</dt><dd><tt>recompute the datalimits based on current artists</tt></dd></dl>
<dl><dt><a name="PolarAxes-scatter"><strong>scatter</strong></a>(self, x, y, s<font color="#909090">=20</font>, c<font color="#909090">='b'</font>, marker<font color="#909090">='o'</font>, cmap<font color="#909090">=None</font>, norm<font color="#909090">=None</font>, vmin<font color="#909090">=None</font>, vmax<font color="#909090">=None</font>, alpha<font color="#909090">=1.0</font>, linewidths<font color="#909090">=None</font>, faceted<font color="#909090">=True</font>, verts<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SCATTER(x, y, s=20, c='b', marker='o', cmap=None, norm=None,<br>
vmin=None, vmax=None, alpha=1.0, linewidths=None,<br>
faceted=True, **kwargs)<br>
Supported function signatures:<br>
SCATTER(x, y, **kwargs)<br>
SCATTER(x, y, s, **kwargs)<br>
SCATTER(x, y, s, c, **kwargs)<br>
Make a scatter plot of x versus y, where x, y are 1-D sequences<br>
of the same length, N.<br>
Arguments s and c can also be given as kwargs; this is encouraged<br>
for readability.<br>
s is a size in points^2. It is a scalar<br>
or an array of the same length as x and y.<br>
c is a color and can be a single color format string,<br>
or a sequence of color specifications of length N,<br>
or a sequence of N numbers to be mapped to colors<br>
using the cmap and norm specified via kwargs (see below).<br>
Note that c should not be a single numeric RGB or RGBA<br>
sequence because that is indistinguishable from an array<br>
of values to be colormapped. c can be a 2-D array in which<br>
the rows are RGB or RGBA, however.<br>
The marker can be one of<br>
's' : square<br>
'o' : circle<br>
'^' : triangle up<br>
'>' : triangle right<br>
'v' : triangle down<br>
'<' : triangle left<br>
'd' : diamond<br>
'p' : pentagram<br>
'h' : hexagon<br>
'8' : octagon<br>
If marker is None and verts is not None, verts is a sequence<br>
of (x,y) vertices for a custom scatter symbol.<br>
s is a size argument in points squared.<br>
Any or all of x, y, s, and c may be masked arrays, in which<br>
case all masks will be combined and only unmasked points<br>
will be plotted.<br>
Other keyword args; the color mapping and normalization arguments will<br>
on be used if c is an array of floats<br>
* cmap = cm.jet : a colors.Colormap instance from matplotlib.cm.<br>
defaults to rc image.cmap<br>
* norm = Normalize() : matplotlib.colors.Normalize instance<br>
is used to scale luminance data to 0,1.<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used. Note if you pass a norm<br>
instance, your settings for vmin and vmax will be ignored<br>
* alpha =1.0 : the alpha value for the patches<br>
* linewidths, if None, defaults to (lines.linewidth,). Note<br>
that this is a tuple, and if you set the linewidths<br>
argument you must set it as a sequence of floats, as<br>
required by RegularPolyCollection -- see<br>
matplotlib.collections.RegularPolyCollection for details<br>
* faceted: if True, will use the default edgecolor for the<br>
markers. If False, will set the edgecolors to be the same<br>
as the facecolors<br>
Optional kwargs control the PatchCollection properties:<br>
alpha: float<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
edgecolor: matplotlib color arg or sequence of rgba tuples<br>
facecolor: matplotlib color arg or sequence of rgba tuples<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-scatter_classic"><strong>scatter_classic</strong></a>(self, x, y, s<font color="#909090">=None</font>, c<font color="#909090">='b'</font>)</dt><dd><tt>scatter_classic is no longer available; please use scatter.<br>
To help in porting, for comparison to the scatter docstring,<br>
here is the scatter_classic docstring:<br>
<br>
SCATTER_CLASSIC(x, y, s=None, c='b')<br>
<br>
Make a scatter plot of x versus y. s is a size (in data coords) and<br>
can be either a scalar or an array of the same length as x or y. c is<br>
a color and can be a single color format string or an length(x) array<br>
of intensities which will be mapped by the colormap jet.<br>
<br>
If size is None a default size will be used</tt></dd></dl>
<dl><dt><a name="PolarAxes-semilogx"><strong>semilogx</strong></a>(self, *args, **kwargs)</dt><dd><tt>SEMILOGX(*args, **kwargs)<br>
Make a semilog plot with log scaling on the x axis. The args to<br>
semilog x are the same as the args to plot. See help plot for more<br>
info.<br>
Optional keyword args supported are any of the kwargs supported by<br>
plot or set_xscale. Notable, for log scaling:<br>
* basex: base of the logarithm<br>
* subsx: the location of the minor ticks; None defaults to<br>
autosubs, which depend on the number of decades in the<br>
plot; see set_xscale for details<br>
The remaining valid kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-semilogy"><strong>semilogy</strong></a>(self, *args, **kwargs)</dt><dd><tt>SEMILOGY(*args, **kwargs):<br>
Make a semilog plot with log scaling on the y axis. The args to<br>
semilogy are the same as the args to plot. See help plot for more<br>
info.<br>
Optional keyword args supported are any of the kwargs supported by<br>
plot or set_yscale. Notable, for log scaling:<br>
* basey: base of the logarithm<br>
* subsy: a sequence of the location of the minor ticks;<br>
None defaults to autosubs, which depend on the number of<br>
decades in the plot; see set_yscale for details<br>
The remaining valid kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_adjustable"><strong>set_adjustable</strong></a>(self, adjustable)</dt><dd><tt>ACCEPTS: ['box' | 'datalim']</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_anchor"><strong>set_anchor</strong></a>(self, anchor)</dt><dd><tt>ACCEPTS: ['C', 'SW', 'S', 'SE', 'E', 'NE', 'N', 'NW', 'W']</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_aspect"><strong>set_aspect</strong></a>(self, aspect, adjustable<font color="#909090">=None</font>, anchor<font color="#909090">=None</font>)</dt><dd><tt>aspect:<br>
'auto' - automatic; fill position rectangle with data<br>
'normal' - same as 'auto'; deprecated<br>
'equal' - same scaling from data to plot units for x and y<br>
num - a circle will be stretched such that the height<br>
is num times the width. aspect=1 is the same as<br>
aspect='equal'.<br>
<br>
adjustable:<br>
'box' - change physical size of axes<br>
'datalim' - change xlim or ylim<br>
<br>
anchor:<br>
'C' - centered<br>
'SW' - lower left corner<br>
'S' - middle of bottom edge<br>
'SE' - lower right corner<br>
etc.<br>
<br>
ACCEPTS: ['auto' | 'equal' | aspect_ratio]</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_autoscale_on"><strong>set_autoscale_on</strong></a>(self, b)</dt><dd><tt>Set whether autoscaling is applied on plot commands<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_axis_bgcolor"><strong>set_axis_bgcolor</strong></a>(self, color)</dt><dd><tt>set the axes background color<br>
<br>
ACCEPTS: any matplotlib color - see help(colors)</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_axis_off"><strong>set_axis_off</strong></a>(self)</dt><dd><tt>turn off the axis<br>
<br>
ACCEPTS: void</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_axis_on"><strong>set_axis_on</strong></a>(self)</dt><dd><tt>turn on the axis<br>
<br>
ACCEPTS: void</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_axisbelow"><strong>set_axisbelow</strong></a>(self, b)</dt><dd><tt>Set whether the axis ticks and gridlines are above or below most artists<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_cursor_props"><strong>set_cursor_props</strong></a>(self, *args)</dt><dd><tt>Set the cursor property as<br>
ax.<a href="#PolarAxes-set_cursor_props">set_cursor_props</a>(linewidth, color) OR<br>
ax.<a href="#PolarAxes-set_cursor_props">set_cursor_props</a>((linewidth, color))<br>
<br>
ACCEPTS: a (float, color) tuple</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_figure"><strong>set_figure</strong></a>(self, fig)</dt><dd><tt>Set the <a href="#Axes">Axes</a> figure<br>
<br>
ACCEPTS: a Figure instance</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_frame_on"><strong>set_frame_on</strong></a>(self, b)</dt><dd><tt>Set whether the axes rectangle patch is drawn<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_navigate"><strong>set_navigate</strong></a>(self, b)</dt><dd><tt>Set whether the axes responds to navigation toolbar commands<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_navigate_mode"><strong>set_navigate_mode</strong></a>(self, b)</dt><dd><tt>Set the navigation toolbar button status;<br>
this is not a user-API function.</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_position"><strong>set_position</strong></a>(self, pos, which<font color="#909090">='both'</font>)</dt><dd><tt>Set the axes position with pos = [left, bottom, width, height]<br>
in relative 0,1 coords<br>
<br>
There are two position variables: one which is ultimately<br>
used, but which may be modified by apply_aspect, and a second<br>
which is the starting point for apply_aspect.<br>
<br>
which = 'active' to change the first;<br>
'original' to change the second;<br>
'both' to change both<br>
<br>
ACCEPTS: len(4) sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_title"><strong>set_title</strong></a>(self, label, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_TITLE(label, fontdict=None, **kwargs):<br>
Set the title for the axes. See the text docstring for information<br>
of how override and the optional args work<br>
kwargs are Text properties:<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_xscale"><strong>set_xscale</strong></a>(self, value, basex<font color="#909090">=10</font>, subsx<font color="#909090">=None</font>)</dt><dd><tt>SET_XSCALE(value, basex=10, subsx=None)<br>
<br>
Set the xscaling: 'log' or 'linear'<br>
<br>
If value is 'log', the additional kwargs have the following meaning<br>
<br>
* basex: base of the logarithm<br>
<br>
* subsx: a sequence of the location of the minor ticks;<br>
None defaults to autosubs, which depend on the number of<br>
decades in the plot. Eg for base 10, subsx=(1,2,5) will<br>
put minor ticks on 1,2,5,11,12,15,21, ....To turn off<br>
minor ticking, set subsx=[]<br>
<br>
ACCEPTS: ['log' | 'linear' ]</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_xticklabels"><strong>set_xticklabels</strong></a>(self, labels, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_XTICKLABELS(labels, fontdict=None, **kwargs)<br>
Set the xtick labels with list of strings labels Return a list of axis<br>
text instances.<br>
kwargs set the Text properties. Valid properties are<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: sequence of strings</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_xticks"><strong>set_xticks</strong></a>(self, ticks)</dt><dd><tt>Set the x ticks with list of ticks<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_yscale"><strong>set_yscale</strong></a>(self, value, basey<font color="#909090">=10</font>, subsy<font color="#909090">=None</font>)</dt><dd><tt>SET_YSCALE(value, basey=10, subsy=None)<br>
<br>
Set the yscaling: 'log' or 'linear'<br>
<br>
If value is 'log', the additional kwargs have the following meaning<br>
<br>
* basey: base of the logarithm<br>
<br>
* subsy: a sequence of the location of the minor ticks;<br>
None defaults to autosubs, which depend on the number of<br>
decades in the plot. Eg for base 10, subsy=(1,2,5) will<br>
put minor ticks on 1,2,5,11,12,15, 21, ....To turn off<br>
minor ticking, set subsy=[]<br>
<br>
ACCEPTS: ['log' | 'linear']</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_yticklabels"><strong>set_yticklabels</strong></a>(self, labels, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_YTICKLABELS(labels, fontdict=None, **kwargs)<br>
Set the ytick labels with list of strings labels. Return a list of<br>
Text instances.<br>
kwargs set Text properties for the labels. Valid properties are<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: sequence of strings</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_yticks"><strong>set_yticks</strong></a>(self, ticks)</dt><dd><tt>Set the y ticks with list of ticks<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarAxes-specgram"><strong>specgram</strong></a>(self, x, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, window<font color="#909090">=<function window_hanning at 0xb5bc7764></font>, noverlap<font color="#909090">=128</font>, cmap<font color="#909090">=None</font>, xextent<font color="#909090">=None</font>)</dt><dd><tt>SPECGRAM(x, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=128,<br>
cmap=None, xextent=None)<br>
<br>
Compute a spectrogram of data in x. Data are split into NFFT length<br>
segements and the PSD of each section is computed. The windowing<br>
function window is applied to each segment, and the amount of overlap<br>
of each segment is specified with noverlap.<br>
<br>
* cmap is a colormap; if None use default determined by rc<br>
<br>
* xextent is the image extent in the xaxes xextent=xmin, xmax -<br>
default 0, max(bins), 0, max(freqs) where bins is the return<br>
value from matplotlib.matplotlib.mlab.specgram<br>
<br>
* See help(psd) for information on the other keyword arguments.<br>
<br>
Return value is (Pxx, freqs, bins, im), where<br>
<br>
bins are the time points the spectrogram is calculated over<br>
<br>
freqs is an array of frequencies<br>
<br>
Pxx is a len(times) x len(freqs) array of power<br>
<br>
im is a matplotlib.image.AxesImage.<br>
<br>
Note: If x is real (i.e. non-complex) only the positive spectrum is<br>
shown. If x is complex both positive and negative parts of the<br>
spectrum are shown.</tt></dd></dl>
<dl><dt><a name="PolarAxes-spy"><strong>spy</strong></a>(self, Z, precision<font color="#909090">=None</font>, marker<font color="#909090">=None</font>, markersize<font color="#909090">=None</font>, aspect<font color="#909090">='equal'</font>, **kwargs)</dt><dd><tt><a href="#PolarAxes-spy">spy</a>(Z) plots the sparsity pattern of the 2-D array Z<br>
<br>
If precision is None, any non-zero value will be plotted;<br>
else, values of absolute(Z)>precision will be plotted.<br>
<br>
The array will be plotted as it would be printed, with<br>
the first index (row) increasing down and the second<br>
index (column) increasing to the right.<br>
<br>
By default aspect is 'equal' so that each array element<br>
occupies a square space; set the aspect kwarg to 'auto'<br>
to allow the plot to fill the plot box, or to any scalar<br>
number to specify the aspect ratio of an array element<br>
directly.<br>
<br>
Two plotting styles are available: image or marker. Both<br>
are available for full arrays, but only the marker style<br>
works for scipy.sparse.spmatrix instances.<br>
<br>
If marker and markersize are None, an image will be<br>
returned and any remaining kwargs are passed to imshow;<br>
else, a Line2D object will be returned with the value<br>
of marker determining the marker type, and any remaining<br>
kwargs passed to the axes plot method.<br>
<br>
If marker and markersize are None, useful kwargs include:<br>
cmap<br>
alpha<br>
See documentation for <a href="#PolarAxes-imshow">imshow</a>() for details.<br>
For controlling colors, e.g. cyan background and red marks, use:<br>
cmap = matplotlib.colors.ListedColormap(['c','r'])<br>
<br>
If marker or markersize is not None, useful kwargs include:<br>
marker<br>
markersize<br>
color<br>
See documentation for <a href="#PolarAxes-plot">plot</a>() for details.<br>
<br>
Useful values for marker include:<br>
's' square (default)<br>
'o' circle<br>
'.' point<br>
',' pixel</tt></dd></dl>
<dl><dt><a name="PolarAxes-stem"><strong>stem</strong></a>(self, x, y, linefmt<font color="#909090">='b-'</font>, markerfmt<font color="#909090">='bo'</font>, basefmt<font color="#909090">='r-'</font>)</dt><dd><tt>STEM(x, y, linefmt='b-', markerfmt='bo', basefmt='r-')<br>
<br>
A stem plot plots vertical lines (using linefmt) at each x location<br>
from the baseline to y, and places a marker there using markerfmt. A<br>
horizontal line at 0 is is plotted using basefmt<br>
<br>
Return value is (markerline, stemlines, baseline) .<br>
<br>
See<br>
<a href="http://www.mathworks.com/access/helpdesk/help/techdoc/ref/stem.html">http://www.mathworks.com/access/helpdesk/help/techdoc/ref/stem.html</a><br>
for details and examples/stem_plot.py for a demo.</tt></dd></dl>
<dl><dt><a name="PolarAxes-text"><strong>text</strong></a>(self, x, y, s, fontdict<font color="#909090">=None</font>, withdash<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>TEXT(x, y, s, fontdict=None, **kwargs)<br>
Add text in string s to axis at location x,y (data coords)<br>
fontdict is a dictionary to override the default text properties.<br>
If fontdict is None, the defaults are determined by your rc<br>
parameters.<br>
withdash=True will create a TextWithDash instance instead<br>
of a Text instance.<br>
Individual keyword arguments can be used to override any given<br>
parameter<br>
<a href="#PolarAxes-text">text</a>(x, y, s, fontsize=12)<br>
The default transform specifies that text is in data coords,<br>
alternatively, you can specify text in axis coords (0,0 lower left and<br>
1,1 upper right). The example below places text in the center of the<br>
axes<br>
<a href="#PolarAxes-text">text</a>(0.5, 0.5,'matplotlib',<br>
horizontalalignment='center',<br>
verticalalignment='center',<br>
transform = ax.transAxes,<br>
)<br>
You can put a rectangular box around the text instance (eg to<br>
set a background color) by using the keyword bbox. bbox is a<br>
dictionary of matplotlib.patches.Rectangle properties (see help<br>
for Rectangle for a list of these). For example<br>
<a href="#PolarAxes-text">text</a>(x, y, s, bbox=dict(facecolor='red', alpha=0.5))<br>
Valid kwargs are Text properties<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-ticklabel_format"><strong>ticklabel_format</strong></a>(self, **kwargs)</dt><dd><tt>Convenience method for manipulating the ScalarFormatter<br>
used by default for linear axes.<br>
<br>
kwargs:<br>
style = 'sci' (or 'scientific') or 'plain';<br>
plain turns off scientific notation<br>
axis = 'x', 'y', or 'both'<br>
<br>
Only the major ticks are affected.<br>
If the method is called when the ScalarFormatter is not<br>
the one being used, an AttributeError will be raised with<br>
no additional error message.<br>
<br>
Additional capabilities and/or friendlier error checking may be added.</tt></dd></dl>
<dl><dt><a name="PolarAxes-update_datalim"><strong>update_datalim</strong></a>(self, xys)</dt><dd><tt>Update the data lim bbox with seq of xy tups or equiv. 2-D array</tt></dd></dl>
<dl><dt><a name="PolarAxes-update_datalim_numerix"><strong>update_datalim_numerix</strong></a>(self, x, y)</dt><dd><tt>Update the data lim bbox with seq of xy tups</tt></dd></dl>
<dl><dt><a name="PolarAxes-vlines"><strong>vlines</strong></a>(self, x, ymin, ymax, colors<font color="#909090">='k'</font>, linestyle<font color="#909090">='solid'</font>, label<font color="#909090">=''</font>, **kwargs)</dt><dd><tt>VLINES(x, ymin, ymax, color='k')<br>
Plot vertical lines at each x from ymin to ymax. ymin or ymax can be<br>
scalars or len(x) numpy arrays. If they are scalars, then the<br>
respective values are constant, else the heights of the lines are<br>
determined by ymin and ymax<br>
colors is a line collections color args, either a single color<br>
or a len(x) list of colors<br>
linestyle is one of solid|dashed|dashdot|dotted<br>
Returns the LineCollection that was added<br>
kwargs are LineCollection properties:<br>
alpha: float or sequence of floats<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle: ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
segments: unknown<br>
transform: a matplotlib.transform transformation instance<br>
verts: unknown<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-xaxis_date"><strong>xaxis_date</strong></a>(self, tz<font color="#909090">=None</font>)</dt><dd><tt>Sets up x-axis ticks and labels that treat the x data as dates.<br>
<br>
tz is the time zone to use in labeling dates. Defaults to rc value.</tt></dd></dl>
<dl><dt><a name="PolarAxes-xcorr"><strong>xcorr</strong></a>(self, x, y, normed<font color="#909090">=False</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, usevlines<font color="#909090">=False</font>, maxlags<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>XCORR(x, y, normed=False, detrend=detrend_none, usevlines=False, **kwargs):<br>
Plot the cross correlation between x and y. If normed=True,<br>
normalize the data but the cross correlation at 0-th lag. x<br>
and y are detrended by the detrend callable (default no<br>
normalization. x and y must be equal length<br>
data are plotted as <a href="#PolarAxes-plot">plot</a>(lags, c, **kwargs)<br>
return value is lags, c, line where lags are a length<br>
2*maxlags+1 lag vector, c is the 2*maxlags+1 auto correlation<br>
vector, and line is a Line2D instance returned by plot. The<br>
default linestyle is None and the default marker is 'o',<br>
though these can be overridden with keyword args. The cross<br>
correlation is performed with numerix cross_correlate with<br>
mode=2.<br>
If usevlines is True, <a href="#Axes">Axes</a>.vlines rather than <a href="#Axes">Axes</a>.plot is used<br>
to draw vertical lines from the origin to the acorr.<br>
Otherwise the plotstyle is determined by the kwargs, which are<br>
Line2D properties. If usevlines, the return value is lags, c,<br>
linecol, b where linecol is the LineCollection and b is the x-axis<br>
if usevlines=True, kwargs are passed onto <a href="#Axes">Axes</a>.vlines<br>
if usevlines=False, kwargs are passed onto <a href="#Axes">Axes</a>.plot<br>
maxlags is a positive integer detailing the number of lags to show.<br>
The default value of None will return all (2*len(x)-1) lags.<br>
See the respective function for documentation on valid kwargs</tt></dd></dl>
<dl><dt><a name="PolarAxes-yaxis_date"><strong>yaxis_date</strong></a>(self, tz<font color="#909090">=None</font>)</dt><dd><tt>Sets up y-axis ticks and labels that treat the y data as dates.<br>
<br>
tz is the time zone to use in labeling dates. Defaults to rc value.</tt></dd></dl>
<dl><dt><a name="PolarAxes-zoomx"><strong>zoomx</strong></a>(self, numsteps)</dt><dd><tt>Zoom in on the x xaxis numsteps (plus for zoom in, minus for zoom out)</tt></dd></dl>
<dl><dt><a name="PolarAxes-zoomy"><strong>zoomy</strong></a>(self, numsteps)</dt><dd><tt>Zoom in on the x xaxis numsteps (plus for zoom in, minus for zoom out)</tt></dd></dl>
<hr>
Data and other attributes inherited from <a href="matplotlib.axes.html#Axes">Axes</a>:<br>
<dl><dt><strong>scaled</strong> = {0: 'linear', 1: 'log'}</dl>
<hr>
Methods inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><a name="PolarAxes-add_callback"><strong>add_callback</strong></a>(self, func)</dt></dl>
<dl><dt><a name="PolarAxes-convert_xunits"><strong>convert_xunits</strong></a>(self, x)</dt><dd><tt>for artists in an axes, if the xaxis as units support,<br>
convert x using xaxis unit type</tt></dd></dl>
<dl><dt><a name="PolarAxes-convert_yunits"><strong>convert_yunits</strong></a>(self, y)</dt><dd><tt>for artists in an axes, if the yaxis as units support,<br>
convert y using yaxis unit type</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_alpha"><strong>get_alpha</strong></a>(self)</dt><dd><tt>Return the alpha value used for blending - not supported on all<br>
backends</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_animated"><strong>get_animated</strong></a>(self)</dt><dd><tt>return the artist's animated state</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_axes"><strong>get_axes</strong></a>(self)</dt><dd><tt>return the axes instance the artist resides in, or None</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_clip_box"><strong>get_clip_box</strong></a>(self)</dt><dd><tt>Return artist clipbox</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_clip_on"><strong>get_clip_on</strong></a>(self)</dt><dd><tt>Return whether artist uses clipping</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_clip_path"><strong>get_clip_path</strong></a>(self)</dt><dd><tt>Return artist clip path</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_figure"><strong>get_figure</strong></a>(self)</dt><dd><tt>return the figure instance</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_label"><strong>get_label</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarAxes-get_picker"><strong>get_picker</strong></a>(self)</dt><dd><tt>return the Pickeration instance used by this artist</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_transform"><strong>get_transform</strong></a>(self)</dt><dd><tt>return the Transformation instance used by this artist</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_visible"><strong>get_visible</strong></a>(self)</dt><dd><tt>return the artist's visiblity</tt></dd></dl>
<dl><dt><a name="PolarAxes-get_zorder"><strong>get_zorder</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarAxes-have_units"><strong>have_units</strong></a>(self)</dt><dd><tt>return True if units are set on the x or y axes</tt></dd></dl>
<dl><dt><a name="PolarAxes-is_figure_set"><strong>is_figure_set</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarAxes-is_transform_set"><strong>is_transform_set</strong></a>(self)</dt><dd><tt><a href="matplotlib.artist.html#Artist">Artist</a> has transform explicity let</tt></dd></dl>
<dl><dt><a name="PolarAxes-pchanged"><strong>pchanged</strong></a>(self)</dt><dd><tt>fire event when property changed</tt></dd></dl>
<dl><dt><a name="PolarAxes-pickable"><strong>pickable</strong></a>(self)</dt><dd><tt>return True if self is pickable</tt></dd></dl>
<dl><dt><a name="PolarAxes-remove_callback"><strong>remove_callback</strong></a>(self, oid)</dt></dl>
<dl><dt><a name="PolarAxes-set"><strong>set</strong></a>(self, **kwargs)</dt><dd><tt>A tkstyle set command, pass kwargs to set properties</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_alpha"><strong>set_alpha</strong></a>(self, alpha)</dt><dd><tt>Set the alpha value used for blending - not supported on<br>
all backends<br>
<br>
ACCEPTS: float</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_animated"><strong>set_animated</strong></a>(self, b)</dt><dd><tt>set the artist's animation state<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_axes"><strong>set_axes</strong></a>(self, axes)</dt><dd><tt>set the axes instance the artist resides in, if any<br>
<br>
ACCEPTS: an axes instance</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_clip_box"><strong>set_clip_box</strong></a>(self, clipbox)</dt><dd><tt>Set the artist's clip Bbox<br>
<br>
ACCEPTS: a matplotlib.transform.Bbox instance</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_clip_on"><strong>set_clip_on</strong></a>(self, b)</dt><dd><tt>Set whether artist uses clipping<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_clip_path"><strong>set_clip_path</strong></a>(self, path)</dt><dd><tt>Set the artist's clip path<br>
<br>
ACCEPTS: an agg.path_storage instance</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_label"><strong>set_label</strong></a>(self, s)</dt><dd><tt>Set the line label to s for auto legend<br>
<br>
ACCEPTS: any string</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_lod"><strong>set_lod</strong></a>(self, on)</dt><dd><tt>Set Level of Detail on or off. If on, the artists may examine<br>
things like the pixel width of the axes and draw a subset of<br>
their contents accordingly<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_picker"><strong>set_picker</strong></a>(self, picker)</dt><dd><tt>set the epsilon for picking used by this artist<br>
<br>
picker can be one of the following:<br>
<br>
None - picking is disabled for this artist (default)<br>
<br>
boolean - if True then picking will be enabled and the<br>
artist will fire a pick event if the mouse event is over<br>
the artist<br>
<br>
float - if picker is a number it is interpreted as an<br>
epsilon tolerance in points and the the artist will fire<br>
off an event if it's data is within epsilon of the mouse<br>
event. For some artists like lines and patch collections,<br>
the artist may provide additional data to the pick event<br>
that is generated, eg the indices of the data within<br>
epsilon of the pick event<br>
<br>
function - if picker is callable, it is a user supplied<br>
function which determines whether the artist is hit by the<br>
mouse event.<br>
<br>
hit, props = picker(artist, mouseevent)<br>
<br>
to determine the hit test. if the mouse event is over the<br>
artist, return hit=True and props is a dictionary of<br>
properties you want added to the PickEvent attributes<br>
<br>
ACCEPTS: [None|float|boolean|callable]</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_transform"><strong>set_transform</strong></a>(self, t)</dt><dd><tt>set the Transformation instance used by this artist<br>
<br>
ACCEPTS: a matplotlib.transform transformation instance</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_visible"><strong>set_visible</strong></a>(self, b)</dt><dd><tt>set the artist's visiblity<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="PolarAxes-set_zorder"><strong>set_zorder</strong></a>(self, level)</dt><dd><tt>Set the zorder for the artist<br>
<br>
ACCEPTS: any number</tt></dd></dl>
<dl><dt><a name="PolarAxes-update"><strong>update</strong></a>(self, props)</dt></dl>
<dl><dt><a name="PolarAxes-update_from"><strong>update_from</strong></a>(self, other)</dt><dd><tt>copy properties from other to self</tt></dd></dl>
<hr>
Data and other attributes inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><strong>aname</strong> = 'Artist'</dl>
<dl><dt><strong>zorder</strong> = 0</dl>
</td></tr></table> <p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#ffc8d8">
<td colspan=3 valign=bottom> <br>
<font color="#000000" face="helvetica, arial"><a name="PolarSubplot">class <strong>PolarSubplot</strong></a>(<a href="matplotlib.axes.html#SubplotBase">SubplotBase</a>, <a href="matplotlib.axes.html#PolarAxes">PolarAxes</a>)</font></td></tr>
<tr bgcolor="#ffc8d8"><td rowspan=2><tt> </tt></td>
<td colspan=2><tt>Create a polar subplot with<br>
<br>
<a href="#PolarSubplot">PolarSubplot</a>(numRows, numCols, plotNum)<br>
<br>
where plotNum=1 is the first plot number and increasing plotNums<br>
fill rows first. max(plotNum)==numRows*numCols<br>
<br>
You can leave out the commas if numRows<=numCols<=plotNum<10, as<br>
in<br>
<br>
<a href="#Subplot">Subplot</a>(211) # 2 rows, 1 column, first (upper) plot<br> </tt></td></tr>
<tr><td> </td>
<td width="100%"><dl><dt>Method resolution order:</dt>
<dd><a href="matplotlib.axes.html#PolarSubplot">PolarSubplot</a></dd>
<dd><a href="matplotlib.axes.html#SubplotBase">SubplotBase</a></dd>
<dd><a href="matplotlib.axes.html#PolarAxes">PolarAxes</a></dd>
<dd><a href="matplotlib.axes.html#Axes">Axes</a></dd>
<dd><a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a></dd>
</dl>
<hr>
Methods defined here:<br>
<dl><dt><a name="PolarSubplot-__init__"><strong>__init__</strong></a>(self, fig, *args, **kwargs)</dt></dl>
<hr>
Methods inherited from <a href="matplotlib.axes.html#SubplotBase">SubplotBase</a>:<br>
<dl><dt><a name="PolarSubplot-change_geometry"><strong>change_geometry</strong></a>(self, numrows, numcols, num)</dt><dd><tt>change subplot geometry, eg from 1,1,1 to 2,2,3</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_geometry"><strong>get_geometry</strong></a>(self)</dt><dd><tt>get the subplot geometry, eg 2,2,3</tt></dd></dl>
<dl><dt><a name="PolarSubplot-is_first_col"><strong>is_first_col</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarSubplot-is_first_row"><strong>is_first_row</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarSubplot-is_last_col"><strong>is_last_col</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarSubplot-is_last_row"><strong>is_last_row</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarSubplot-label_outer"><strong>label_outer</strong></a>(self)</dt><dd><tt>set the visible property on ticklabels so xticklabels are<br>
visible only if the subplot is in the last row and yticklabels<br>
are visible only if the subplot is in the first column</tt></dd></dl>
<dl><dt><a name="PolarSubplot-update_params"><strong>update_params</strong></a>(self)</dt><dd><tt>update the subplot position from fig.subplotpars</tt></dd></dl>
<hr>
Methods inherited from <a href="matplotlib.axes.html#PolarAxes">PolarAxes</a>:<br>
<dl><dt><a name="PolarSubplot-autoscale_view"><strong>autoscale_view</strong></a>(self, scalex<font color="#909090">=True</font>, scaley<font color="#909090">=True</font>)</dt><dd><tt>set the view limits to include all the data in the axes</tt></dd></dl>
<dl><dt><a name="PolarSubplot-cla"><strong>cla</strong></a>(self)</dt><dd><tt>Clear the current axes</tt></dd></dl>
<dl><dt><a name="PolarSubplot-draw"><strong>draw</strong></a>(self, renderer)</dt></dl>
<dl><dt><a name="PolarSubplot-format_coord"><strong>format_coord</strong></a>(self, theta, r)</dt><dd><tt>return a format string formatting the coordinate</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_children"><strong>get_children</strong></a>(self)</dt><dd><tt>return a list of child artists</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_rmax"><strong>get_rmax</strong></a>(self)</dt><dd><tt>get the maximum radius in the view limits dimension</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_xscale"><strong>get_xscale</strong></a>(self)</dt><dd><tt>return the xaxis scale string</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_yscale"><strong>get_yscale</strong></a>(self)</dt><dd><tt>return the yaxis scale string</tt></dd></dl>
<dl><dt><a name="PolarSubplot-grid"><strong>grid</strong></a>(self, b)</dt><dd><tt>Set the axes grids on or off; b is a boolean</tt></dd></dl>
<dl><dt><a name="PolarSubplot-has_data"><strong>has_data</strong></a>(self)</dt><dd><tt>return true if any artists have been added to axes</tt></dd></dl>
<dl><dt><a name="PolarSubplot-regrid"><strong>regrid</strong></a>(self, rmax)</dt></dl>
<dl><dt><a name="PolarSubplot-set_rgrids"><strong>set_rgrids</strong></a>(self, radii, labels<font color="#909090">=None</font>, angle<font color="#909090">=22.5</font>, rpad<font color="#909090">=0.050000000000000003</font>, **kwargs)</dt><dd><tt>set the radial locations and labels of the r grids<br>
The labels will appear at radial distances radii at angle<br>
labels, if not None, is a len(radii) list of strings of the<br>
labels to use at each angle.<br>
if labels is None, the self.<strong>rformatter</strong> will be used<br>
rpad is a fraction of the max of radii which will pad each of<br>
the radial labels in the radial direction.<br>
<br>
Return value is a list of lines, labels where the lines are<br>
matplotlib.Line2D instances and the labels are matplotlib.Text<br>
instances<br>
kwargs control the rgrid Text label properties:<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_rmax"><strong>set_rmax</strong></a>(self, rmax)</dt></dl>
<dl><dt><a name="PolarSubplot-set_thetagrids"><strong>set_thetagrids</strong></a>(self, angles, labels<font color="#909090">=None</font>, fmt<font color="#909090">='%d'</font>, frac<font color="#909090">=1.1000000000000001</font>, **kwargs)</dt><dd><tt>set the angles at which to place the theta grids (these<br>
gridlines are equal along the theta dimension). angles is in<br>
degrees<br>
labels, if not None, is a len(angles) list of strings of the<br>
labels to use at each angle.<br>
if labels is None, the labels with be fmt%angle<br>
frac is the fraction of the polar axes radius at which to<br>
place the label (1 is the edge).Eg 1.05 isd outside the axes<br>
and 0.95 is inside the axes<br>
Return value is a list of lines, labels where the lines are<br>
matplotlib.Line2D instances and the labels are matplotlib.Text<br>
instances:<br>
kwargs are optional text properties for the labels<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_xlabel"><strong>set_xlabel</strong></a>(self, xlabel, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>xlabel not implemented</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_xlim"><strong>set_xlim</strong></a>(self, xmin<font color="#909090">=None</font>, xmax<font color="#909090">=None</font>, emit<font color="#909090">=True</font>)</dt><dd><tt>set the xlimits<br>
ACCEPTS: len(2) sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_ylabel"><strong>set_ylabel</strong></a>(self, ylabel, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>ylabel not implemented</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_ylim"><strong>set_ylim</strong></a>(self, ymin<font color="#909090">=None</font>, ymax<font color="#909090">=None</font>, emit<font color="#909090">=True</font>)</dt><dd><tt>set the ylimits<br>
ACCEPTS: len(2) sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarSubplot-table"><strong>table</strong></a>(self, *args, **kwargs)</dt><dd><tt>TABLE(*args, **kwargs)<br>
Not implemented for polar axes</tt></dd></dl>
<dl><dt><a name="PolarSubplot-toggle_log_lineary"><strong>toggle_log_lineary</strong></a>(self)</dt><dd><tt>toggle between log and linear axes ignored for polar</tt></dd></dl>
<hr>
Data and other attributes inherited from <a href="matplotlib.axes.html#PolarAxes">PolarAxes</a>:<br>
<dl><dt><strong>RESOLUTION</strong> = 100</dl>
<hr>
Methods inherited from <a href="matplotlib.axes.html#Axes">Axes</a>:<br>
<dl><dt><a name="PolarSubplot-acorr"><strong>acorr</strong></a>(self, x, **kwargs)</dt><dd><tt>ACORR(x, normed=False, detrend=detrend_none, usevlines=False,<br>
maxlags=None, **kwargs)<br>
Plot the autocorrelation of x. If normed=True, normalize the<br>
data but the autocorrelation at 0-th lag. x is detrended by<br>
the detrend callable (default no normalization.<br>
data are plotted as <a href="#PolarSubplot-plot">plot</a>(lags, c, **kwargs)<br>
return value is lags, c, line where lags are a length<br>
2*maxlags+1 lag vector, c is the 2*maxlags+1 auto correlation<br>
vector, and line is a Line2D instance returned by plot. The<br>
default linestyle is None and the default marker is 'o',<br>
though these can be overridden with keyword args. The cross<br>
correlation is performed with numerix cross_correlate with<br>
mode=2.<br>
If usevlines is True, <a href="#Axes">Axes</a>.vlines rather than <a href="#Axes">Axes</a>.plot is used<br>
to draw vertical lines from the origin to the acorr.<br>
Otherwise the plotstyle is determined by the kwargs, which are<br>
Line2D properties. If usevlines, the return value is lags, c,<br>
linecol, b where linecol is the LineCollection and b is the x-axis<br>
if usevlines=True, kwargs are passed onto <a href="#Axes">Axes</a>.vlines<br>
if usevlines=False, kwargs are passed onto <a href="#Axes">Axes</a>.plot<br>
maxlags is a positive integer detailing the number of lags to show.<br>
The default value of None will return all (2*len(x)-1) lags.<br>
See the respective function for documentation on valid kwargs</tt></dd></dl>
<dl><dt><a name="PolarSubplot-add_artist"><strong>add_artist</strong></a>(self, a)</dt><dd><tt>Add any artist to the axes</tt></dd></dl>
<dl><dt><a name="PolarSubplot-add_collection"><strong>add_collection</strong></a>(self, collection, autolim<font color="#909090">=False</font>)</dt><dd><tt>add a Collection instance to <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="PolarSubplot-add_line"><strong>add_line</strong></a>(self, line)</dt><dd><tt>Add a line to the list of plot lines</tt></dd></dl>
<dl><dt><a name="PolarSubplot-add_patch"><strong>add_patch</strong></a>(self, p)</dt><dd><tt>Add a patch to the list of <a href="#Axes">Axes</a> patches; the clipbox will be<br>
set to the <a href="#Axes">Axes</a> clipping box. If the transform is not set, it<br>
wil be set to self.<strong>transData</strong>.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-add_table"><strong>add_table</strong></a>(self, tab)</dt><dd><tt>Add a table instance to the list of axes tables</tt></dd></dl>
<dl><dt><a name="PolarSubplot-annotate"><strong>annotate</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#PolarSubplot-annotate">annotate</a>(self, s, xy, textloc,<br>
xycoords='data', textcoords='data',<br>
lineprops=None,<br>
markerprops=None<br>
**props)<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-apply_aspect"><strong>apply_aspect</strong></a>(self, data_ratio<font color="#909090">=None</font>)</dt><dd><tt>Use self.<strong>_aspect</strong> and self.<strong>_adjustable</strong> to modify the<br>
axes box or the view limits.<br>
The data_ratio kwarg is set to 1 for polar axes. It is<br>
used only when _adjustable is 'box'.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-arrow"><strong>arrow</strong></a>(self, x, y, dx, dy, **kwargs)</dt><dd><tt>Draws arrow on specified axis from (x,y) to (x+dx,y+dy).<br>
Optional kwargs control the arrow properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-axhline"><strong>axhline</strong></a>(self, y<font color="#909090">=0</font>, xmin<font color="#909090">=0</font>, xmax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXHLINE(y=0, xmin=0, xmax=1, **kwargs)<br>
Axis Horizontal Line<br>
Draw a horizontal line at y from xmin to xmax. With the default<br>
values of xmin=0 and xmax=1, this line will always span the horizontal<br>
extent of the axes, regardless of the xlim settings, even if you<br>
change them, eg with the xlim command. That is, the horizontal extent<br>
is in axes coords: 0=left, 0.5=middle, 1.0=right but the y location is<br>
in data coordinates.<br>
Return value is the Line2D instance. kwargs are the same as kwargs to<br>
plot, and can be used to control the line properties. Eg<br>
# draw a thick red hline at y=0 that spans the xrange<br>
<a href="#PolarSubplot-axhline">axhline</a>(linewidth=4, color='r')<br>
# draw a default hline at y=1 that spans the xrange<br>
<a href="#PolarSubplot-axhline">axhline</a>(y=1)<br>
# draw a default hline at y=.5 that spans the the middle half of<br>
# the xrange<br>
<a href="#PolarSubplot-axhline">axhline</a>(y=.5, xmin=0.25, xmax=0.75)<br>
Valid kwargs are Line2D properties<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-axhspan"><strong>axhspan</strong></a>(self, ymin, ymax, xmin<font color="#909090">=0</font>, xmax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXHSPAN(ymin, ymax, xmin=0, xmax=1, **kwargs)<br>
Axis Horizontal Span. ycoords are in data units and x<br>
coords are in axes (relative 0-1) units<br>
Draw a horizontal span (regtangle) from ymin to ymax. With the<br>
default values of xmin=0 and xmax=1, this always span the xrange,<br>
regardless of the xlim settings, even if you change them, eg with the<br>
xlim command. That is, the horizontal extent is in axes coords:<br>
0=left, 0.5=middle, 1.0=right but the y location is in data<br>
coordinates.<br>
kwargs are the kwargs to Patch, eg<br>
antialiased, aa<br>
linewidth, lw<br>
edgecolor, ec<br>
facecolor, fc<br>
the terms on the right are aliases<br>
Return value is the patches.Polygon instance.<br>
#draws a gray rectangle from y=0.25-0.75 that spans the horizontal<br>
#extent of the axes<br>
<a href="#PolarSubplot-axhspan">axhspan</a>(0.25, 0.75, facecolor='0.5', alpha=0.5)<br>
Valid kwargs are Polygon properties<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-axis"><strong>axis</strong></a>(self, *v, **kwargs)</dt><dd><tt>Convenience method for manipulating the x and y view limits<br>
and the aspect ratio of the plot.<br>
<br>
kwargs are passed on to set_xlim and set_ylim -- see their docstrings for details</tt></dd></dl>
<dl><dt><a name="PolarSubplot-axvline"><strong>axvline</strong></a>(self, x<font color="#909090">=0</font>, ymin<font color="#909090">=0</font>, ymax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXVLINE(x=0, ymin=0, ymax=1, **kwargs)<br>
Axis Vertical Line<br>
Draw a vertical line at x from ymin to ymax. With the default values<br>
of ymin=0 and ymax=1, this line will always span the vertical extent<br>
of the axes, regardless of the xlim settings, even if you change them,<br>
eg with the xlim command. That is, the vertical extent is in axes<br>
coords: 0=bottom, 0.5=middle, 1.0=top but the x location is in data<br>
coordinates.<br>
Return value is the Line2D instance. kwargs are the same as<br>
kwargs to plot, and can be used to control the line properties. Eg<br>
# draw a thick red vline at x=0 that spans the yrange<br>
l = <a href="#PolarSubplot-axvline">axvline</a>(linewidth=4, color='r')<br>
# draw a default vline at x=1 that spans the yrange<br>
l = <a href="#PolarSubplot-axvline">axvline</a>(x=1)<br>
# draw a default vline at x=.5 that spans the the middle half of<br>
# the yrange<br>
<a href="#PolarSubplot-axvline">axvline</a>(x=.5, ymin=0.25, ymax=0.75)<br>
Valid kwargs are Line2D properties<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-axvspan"><strong>axvspan</strong></a>(self, xmin, xmax, ymin<font color="#909090">=0</font>, ymax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXVSPAN(xmin, xmax, ymin=0, ymax=1, **kwargs)<br>
axvspan : Axis Vertical Span. xcoords are in data units and y coords<br>
are in axes (relative 0-1) units<br>
Draw a vertical span (regtangle) from xmin to xmax. With the default<br>
values of ymin=0 and ymax=1, this always span the yrange, regardless<br>
of the ylim settings, even if you change them, eg with the ylim<br>
command. That is, the vertical extent is in axes coords: 0=bottom,<br>
0.5=middle, 1.0=top but the y location is in data coordinates.<br>
kwargs are the kwargs to Patch, eg<br>
antialiased, aa<br>
linewidth, lw<br>
edgecolor, ec<br>
facecolor, fc<br>
the terms on the right are aliases<br>
return value is the patches.Polygon instance.<br>
# draw a vertical green translucent rectangle from x=1.25 to 1.55 that<br>
# spans the yrange of the axes<br>
<a href="#PolarSubplot-axvspan">axvspan</a>(1.25, 1.55, facecolor='g', alpha=0.5)<br>
Valid kwargs are Polygon properties<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-bar"><strong>bar</strong></a>(self, left, height, width<font color="#909090">=0.80000000000000004</font>, bottom<font color="#909090">=None</font>, color<font color="#909090">=None</font>, edgecolor<font color="#909090">=None</font>, linewidth<font color="#909090">=None</font>, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, ecolor<font color="#909090">=None</font>, capsize<font color="#909090">=3</font>, align<font color="#909090">='edge'</font>, orientation<font color="#909090">='vertical'</font>, log<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>BAR(left, height, width=0.8, bottom=0,<br>
color=None, edgecolor=None, linewidth=None,<br>
yerr=None, xerr=None, ecolor=None, capsize=3,<br>
align='edge', orientation='vertical', log=False)<br>
Make a bar plot with rectangles bounded by<br>
left, left+width, bottom, bottom+height<br>
(left, right, bottom and top edges)<br>
left, height, width, and bottom can be either scalars or sequences<br>
Return value is a list of Rectangle patch instances<br>
left - the x coordinates of the left sides of the bars<br>
height - the heights of the bars<br>
Optional arguments:<br>
width - the widths of the bars<br>
bottom - the y coordinates of the bottom edges of the bars<br>
color - the colors of the bars<br>
edgecolor - the colors of the bar edges<br>
linewidth - width of bar edges; None means use default<br>
linewidth; 0 means don't draw edges.<br>
xerr and yerr, if not None, will be used to generate errorbars<br>
on the bar chart<br>
ecolor specifies the color of any errorbar<br>
capsize (default 3) determines the length in points of the error<br>
bar caps<br>
align = 'edge' (default) | 'center'<br>
orientation = 'vertical' | 'horizontal'<br>
log = False | True - False (default) leaves the orientation<br>
axis as-is; True sets it to log scale<br>
For vertical bars, align='edge' aligns bars by their left edges in<br>
left, while 'center' interprets these values as the x coordinates of<br>
the bar centers. For horizontal bars, 'edge' aligns bars by their<br>
bottom edges in bottom, while 'center' interprets these values as the<br>
y coordinates of the bar centers.<br>
The optional arguments color, edgecolor, linewidth, xerr, and yerr can<br>
be either scalars or sequences of length equal to the number of bars.<br>
This enables you to use bar as the basis for stacked bar charts, or<br>
candlestick plots.<br>
Optional kwargs:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-barh"><strong>barh</strong></a>(self, bottom, width, height<font color="#909090">=0.80000000000000004</font>, left<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>BARH(bottom, width, height=0.8, left=0, **kwargs)<br>
Make a horizontal bar plot with rectangles bounded by<br>
left, left+width, bottom, bottom+height<br>
(left, right, bottom and top edges)<br>
bottom, width, height, and left can be either scalars or sequences<br>
Return value is a list of Rectangle patch instances<br>
bottom - the vertical positions of the bottom edges of the bars<br>
width - the lengths of the bars<br>
Optional arguments:<br>
height - the heights (thicknesses) of the bars<br>
left - the x coordinates of the left edges of the bars<br>
color - the colors of the bars<br>
edgecolor - the colors of the bar edges<br>
linewidth - width of bar edges; None means use default<br>
linewidth; 0 means don't draw edges.<br>
xerr and yerr, if not None, will be used to generate errorbars<br>
on the bar chart<br>
ecolor specifies the color of any errorbar<br>
capsize (default 3) determines the length in points of the error<br>
bar caps<br>
align = 'edge' (default) | 'center'<br>
log = False | True - False (default) leaves the horizontal<br>
axis as-is; True sets it to log scale<br>
Setting align='edge' aligns bars by their bottom edges in bottom,<br>
while 'center' interprets these values as the y coordinates of the bar<br>
centers.<br>
The optional arguments color, edgecolor, linewidth, xerr, and yerr can<br>
be either scalars or sequences of length equal to the number of bars.<br>
This enables you to use barh as the basis for stacked bar charts, or<br>
candlestick plots.<br>
Optional kwargs:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-boxplot"><strong>boxplot</strong></a>(self, x, notch<font color="#909090">=0</font>, sym<font color="#909090">='b+'</font>, vert<font color="#909090">=1</font>, whis<font color="#909090">=1.5</font>, positions<font color="#909090">=None</font>, widths<font color="#909090">=None</font>)</dt><dd><tt><a href="#PolarSubplot-boxplot">boxplot</a>(x, notch=0, sym='+', vert=1, whis=1.5,<br>
positions=None, widths=None)<br>
<br>
Make a box and whisker plot for each column of x or<br>
each vector in sequence x.<br>
The box extends from the lower to upper quartile values<br>
of the data, with a line at the median. The whiskers<br>
extend from the box to show the range of the data. Flier<br>
points are those past the end of the whiskers.<br>
<br>
notch = 0 (default) produces a rectangular box plot.<br>
notch = 1 will produce a notched box plot<br>
<br>
sym (default 'b+') is the default symbol for flier points.<br>
Enter an empty string ('') if you don't want to show fliers.<br>
<br>
vert = 1 (default) makes the boxes vertical.<br>
vert = 0 makes horizontal boxes. This seems goofy, but<br>
that's how Matlab did it.<br>
<br>
whis (default 1.5) defines the length of the whiskers as<br>
a function of the inner quartile range. They extend to the<br>
most extreme data point within ( whis*(75%-25%) ) data range.<br>
<br>
positions (default 1,2,...,n) sets the horizontal positions of<br>
the boxes. The ticks and limits are automatically set to match<br>
the positions.<br>
<br>
widths is either a scalar or a vector and sets the width of<br>
each box. The default is 0.5, or 0.15*(distance between extreme<br>
positions) if that is smaller.<br>
<br>
x is an array or a sequence of vectors.<br>
<br>
Returns a list of the lines added.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-broken_barh"><strong>broken_barh</strong></a>(self, xranges, yrange, **kwargs)</dt><dd><tt>A collection of horizontal bars spanning yrange with a sequence of<br>
xranges<br>
xranges : sequence of (xmin, xwidth)<br>
yrange : (ymin, ywidth)<br>
kwargs are collections.BrokenBarHCollection properties<br>
alpha: float<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
edgecolor: matplotlib color arg or sequence of rgba tuples<br>
facecolor: matplotlib color arg or sequence of rgba tuples<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number<br>
these can either be a single argument, ie facecolors='black'<br>
or a sequence of arguments for the various bars, ie<br>
facecolors='black', 'red', 'green'</tt></dd></dl>
<dl><dt><a name="PolarSubplot-clabel"><strong>clabel</strong></a>(self, CS, *args, **kwargs)</dt><dd><tt><a href="#PolarSubplot-clabel">clabel</a>(CS, **kwargs) - add labels to line contours in CS,<br>
where CS is a ContourSet object returned by contour.<br>
<br>
<a href="#PolarSubplot-clabel">clabel</a>(CS, V, **kwargs) - only label contours listed in V<br>
<br>
keyword arguments:<br>
<br>
* fontsize = None: as described in <a href="http://matplotlib.sf.net/fonts.html">http://matplotlib.sf.net/fonts.html</a><br>
<br>
* colors = None:<br>
<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different labels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all labels<br>
will be plotted in this color<br>
<br>
- if colors == None, the color of each label matches the color<br>
of the corresponding contour<br>
<br>
* inline = True: controls whether the underlying contour is removed<br>
(inline = True) or not (False)<br>
<br>
* fmt = '%1.3f': a format string for the label</tt></dd></dl>
<dl><dt><a name="PolarSubplot-clear"><strong>clear</strong></a>(self)</dt><dd><tt>clear the axes</tt></dd></dl>
<dl><dt><a name="PolarSubplot-cohere"><strong>cohere</strong></a>(self, x, y, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, window<font color="#909090">=<function window_hanning at 0xb5bc7764></font>, noverlap<font color="#909090">=0</font>, **kwargs)</dt><dd><tt>COHERE(x, y, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0, **kwargs)<br>
cohere the coherence between x and y. Coherence is the normalized<br>
cross spectral density<br>
Cxy = |Pxy|^2/(Pxx*Pyy)<br>
The return value is (Cxy, f), where f are the frequencies of the<br>
coherence vector.<br>
See the PSD help for a description of the optional parameters.<br>
kwargs are applied to the lines<br>
Returns the tuple Cxy, freqs<br>
Refs: Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)<br>
kwargs control the Line2D properties of the coherence plot:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-connect"><strong>connect</strong></a>(self, s, func)</dt><dd><tt>Register observers to be notified when certain events occur. Register<br>
with callback functions with the following signatures. The function<br>
has the following signature<br>
<br>
func(ax) # where ax is the instance making the callback.<br>
<br>
The following events can be connected to:<br>
<br>
'xlim_changed','ylim_changed'<br>
<br>
The connection id is is returned - you can use this with<br>
disconnect to disconnect from the axes event</tt></dd></dl>
<dl><dt><a name="PolarSubplot-contour"><strong>contour</strong></a>(self, *args, **kwargs)</dt><dd><tt>contour and contourf draw contour lines and filled contours,<br>
respectively. Except as noted, function signatures and return<br>
values are the same for both versions.<br>
<br>
contourf differs from the Matlab (TM) version in that it does not<br>
draw the polygon edges, because the contouring engine yields<br>
simply connected regions with branch cuts. To draw the edges,<br>
add line contours with calls to contour.<br>
<br>
<br>
Function signatures<br>
<br>
<a href="#PolarSubplot-contour">contour</a>(Z) - make a contour plot of an array Z. The level<br>
values are chosen automatically.<br>
<br>
<a href="#PolarSubplot-contour">contour</a>(X,Y,Z) - X,Y specify the (x,y) coordinates of the surface<br>
<br>
<a href="#PolarSubplot-contour">contour</a>(Z,N) and <a href="#PolarSubplot-contour">contour</a>(X,Y,Z,N) - contour N automatically-chosen<br>
levels.<br>
<br>
<a href="#PolarSubplot-contour">contour</a>(Z,V) and <a href="#PolarSubplot-contour">contour</a>(X,Y,Z,V) - draw len(V) contour lines,<br>
at the values specified in sequence V<br>
<br>
<a href="#PolarSubplot-contourf">contourf</a>(..., V) - fill the (len(V)-1) regions between the<br>
values in V<br>
<br>
<a href="#PolarSubplot-contour">contour</a>(Z, **kwargs) - Use keyword args to control colors, linewidth,<br>
origin, cmap ... see below<br>
<br>
X, Y, and Z must be arrays with the same dimensions.<br>
Z may be a masked array, but filled contouring may not handle<br>
internal masked regions correctly.<br>
<br>
C = <a href="#PolarSubplot-contour">contour</a>(...) returns a ContourSet object.<br>
<br>
<br>
Optional keyword args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* colors = None; or one of the following:<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different levels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all levels<br>
will be plotted in this color<br>
<br>
- if colors == None, the colormap specified by cmap will be used<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
* cmap = None: a cm Colormap instance from matplotlib.cm.<br>
- if cmap == None and colors == None, a default Colormap is used.<br>
<br>
* norm = None: a matplotlib.colors.Normalize instance for<br>
scaling data values to colors.<br>
- if norm == None, and colors == None, the default<br>
linear scaling is used.<br>
<br>
* origin = None: 'upper'|'lower'|'image'|None.<br>
If 'image', the rc value for image.origin will be used.<br>
If None (default), the first value of Z will correspond<br>
to the lower left corner, location (0,0).<br>
This keyword is active only if contourf is called with<br>
one or two arguments, that is, without explicitly<br>
specifying X and Y.<br>
<br>
* extent = None: (x0,x1,y0,y1); also active only if X and Y<br>
are not specified. If origin is not None, then extent is<br>
interpreted as in imshow: it gives the outer pixel boundaries.<br>
In this case, the position of Z[0,0] is the center of the<br>
pixel, not a corner.<br>
If origin is None, then (x0,y0) is the position of Z[0,0],<br>
and (x1,y1) is the position of Z[-1,-1].<br>
<br>
* locator = None: an instance of a ticker.Locator subclass;<br>
default is MaxNLocator. It is used to determine the<br>
contour levels if they are not given explicitly via the<br>
V argument.<br>
<br>
***** New: *****<br>
* extend = 'neither', 'both', 'min', 'max'<br>
Unless this is 'neither' (default), contour levels are<br>
automatically added to one or both ends of the range so that<br>
all data are included. These added ranges are then<br>
mapped to the special colormap values which default to<br>
the ends of the colormap range, but can be set via<br>
Colormap.set_under() and Colormap.set_over() methods.<br>
To replace clip_ends=True and V = [-100, 2, 1, 0, 1, 2, 100],<br>
use extend='both' and V = [2, 1, 0, 1, 2].<br>
****************<br>
<br>
contour only:<br>
* linewidths = None: or one of these:<br>
- a number - all levels will be plotted with this linewidth,<br>
e.g. linewidths = 0.6<br>
<br>
- a tuple of numbers, e.g. linewidths = (0.4, 0.8, 1.2) different<br>
levels will be plotted with different linewidths in the order<br>
specified<br>
<br>
- if linewidths == None, the default width in lines.linewidth in<br>
matplotlibrc is used<br>
<br>
contourf only:<br>
***** Obsolete: ****<br>
* clip_ends = True<br>
If False, the limits for color scaling are set to the<br>
minimum and maximum contour levels.<br>
True (default) clips the scaling limits. Example:<br>
if the contour boundaries are V = [-100, 2, 1, 0, 1, 2, 100],<br>
then the scaling limits will be [-100, 100] if clip_ends<br>
is False, and [-3, 3] if clip_ends is True.<br>
* linewidths = None or a number; default of 0.05 works for<br>
Postscript; a value of about 0.5 seems better for Agg.<br>
* antialiased = True (default) or False; if False, there is<br>
no need to increase the linewidths for Agg, but True gives<br>
nicer color boundaries. If antialiased is True and linewidths<br>
is too small, then there may be light-colored lines at the<br>
color boundaries caused by the antialiasing.<br>
* nchunk = 0 (default) for no subdivision of the domain;<br>
specify a positive integer to divide the domain into<br>
subdomains of roughly nchunk by nchunk points. This may<br>
never actually be advantageous, so this option may be<br>
removed. Chunking introduces artifacts at the chunk<br>
boundaries unless antialiased = False, or linewidths is<br>
set to a large enough value for the particular renderer and<br>
resolution.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-contourf"><strong>contourf</strong></a>(self, *args, **kwargs)</dt><dd><tt>contour and contourf draw contour lines and filled contours,<br>
respectively. Except as noted, function signatures and return<br>
values are the same for both versions.<br>
<br>
contourf differs from the Matlab (TM) version in that it does not<br>
draw the polygon edges, because the contouring engine yields<br>
simply connected regions with branch cuts. To draw the edges,<br>
add line contours with calls to contour.<br>
<br>
<br>
Function signatures<br>
<br>
<a href="#PolarSubplot-contour">contour</a>(Z) - make a contour plot of an array Z. The level<br>
values are chosen automatically.<br>
<br>
<a href="#PolarSubplot-contour">contour</a>(X,Y,Z) - X,Y specify the (x,y) coordinates of the surface<br>
<br>
<a href="#PolarSubplot-contour">contour</a>(Z,N) and <a href="#PolarSubplot-contour">contour</a>(X,Y,Z,N) - contour N automatically-chosen<br>
levels.<br>
<br>
<a href="#PolarSubplot-contour">contour</a>(Z,V) and <a href="#PolarSubplot-contour">contour</a>(X,Y,Z,V) - draw len(V) contour lines,<br>
at the values specified in sequence V<br>
<br>
<a href="#PolarSubplot-contourf">contourf</a>(..., V) - fill the (len(V)-1) regions between the<br>
values in V<br>
<br>
<a href="#PolarSubplot-contour">contour</a>(Z, **kwargs) - Use keyword args to control colors, linewidth,<br>
origin, cmap ... see below<br>
<br>
X, Y, and Z must be arrays with the same dimensions.<br>
Z may be a masked array, but filled contouring may not handle<br>
internal masked regions correctly.<br>
<br>
C = <a href="#PolarSubplot-contour">contour</a>(...) returns a ContourSet object.<br>
<br>
<br>
Optional keyword args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* colors = None; or one of the following:<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different levels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all levels<br>
will be plotted in this color<br>
<br>
- if colors == None, the colormap specified by cmap will be used<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
* cmap = None: a cm Colormap instance from matplotlib.cm.<br>
- if cmap == None and colors == None, a default Colormap is used.<br>
<br>
* norm = None: a matplotlib.colors.Normalize instance for<br>
scaling data values to colors.<br>
- if norm == None, and colors == None, the default<br>
linear scaling is used.<br>
<br>
* origin = None: 'upper'|'lower'|'image'|None.<br>
If 'image', the rc value for image.origin will be used.<br>
If None (default), the first value of Z will correspond<br>
to the lower left corner, location (0,0).<br>
This keyword is active only if contourf is called with<br>
one or two arguments, that is, without explicitly<br>
specifying X and Y.<br>
<br>
* extent = None: (x0,x1,y0,y1); also active only if X and Y<br>
are not specified. If origin is not None, then extent is<br>
interpreted as in imshow: it gives the outer pixel boundaries.<br>
In this case, the position of Z[0,0] is the center of the<br>
pixel, not a corner.<br>
If origin is None, then (x0,y0) is the position of Z[0,0],<br>
and (x1,y1) is the position of Z[-1,-1].<br>
<br>
* locator = None: an instance of a ticker.Locator subclass;<br>
default is MaxNLocator. It is used to determine the<br>
contour levels if they are not given explicitly via the<br>
V argument.<br>
<br>
***** New: *****<br>
* extend = 'neither', 'both', 'min', 'max'<br>
Unless this is 'neither' (default), contour levels are<br>
automatically added to one or both ends of the range so that<br>
all data are included. These added ranges are then<br>
mapped to the special colormap values which default to<br>
the ends of the colormap range, but can be set via<br>
Colormap.set_under() and Colormap.set_over() methods.<br>
To replace clip_ends=True and V = [-100, 2, 1, 0, 1, 2, 100],<br>
use extend='both' and V = [2, 1, 0, 1, 2].<br>
****************<br>
<br>
contour only:<br>
* linewidths = None: or one of these:<br>
- a number - all levels will be plotted with this linewidth,<br>
e.g. linewidths = 0.6<br>
<br>
- a tuple of numbers, e.g. linewidths = (0.4, 0.8, 1.2) different<br>
levels will be plotted with different linewidths in the order<br>
specified<br>
<br>
- if linewidths == None, the default width in lines.linewidth in<br>
matplotlibrc is used<br>
<br>
contourf only:<br>
***** Obsolete: ****<br>
* clip_ends = True<br>
If False, the limits for color scaling are set to the<br>
minimum and maximum contour levels.<br>
True (default) clips the scaling limits. Example:<br>
if the contour boundaries are V = [-100, 2, 1, 0, 1, 2, 100],<br>
then the scaling limits will be [-100, 100] if clip_ends<br>
is False, and [-3, 3] if clip_ends is True.<br>
* linewidths = None or a number; default of 0.05 works for<br>
Postscript; a value of about 0.5 seems better for Agg.<br>
* antialiased = True (default) or False; if False, there is<br>
no need to increase the linewidths for Agg, but True gives<br>
nicer color boundaries. If antialiased is True and linewidths<br>
is too small, then there may be light-colored lines at the<br>
color boundaries caused by the antialiasing.<br>
* nchunk = 0 (default) for no subdivision of the domain;<br>
specify a positive integer to divide the domain into<br>
subdomains of roughly nchunk by nchunk points. This may<br>
never actually be advantageous, so this option may be<br>
removed. Chunking introduces artifacts at the chunk<br>
boundaries unless antialiased = False, or linewidths is<br>
set to a large enough value for the particular renderer and<br>
resolution.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-csd"><strong>csd</strong></a>(self, x, y, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, window<font color="#909090">=<function window_hanning at 0xb5bc7764></font>, noverlap<font color="#909090">=0</font>, **kwargs)</dt><dd><tt>CSD(x, y, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0, **kwargs)<br>
The cross spectral density Pxy by Welches average periodogram method.<br>
The vectors x and y are divided into NFFT length segments. Each<br>
segment is detrended by function detrend and windowed by function<br>
window. The product of the direct FFTs of x and y are averaged over<br>
each segment to compute Pxy, with a scaling to correct for power loss<br>
due to windowing.<br>
See the PSD help for a description of the optional parameters.<br>
Returns the tuple Pxy, freqs. Pxy is the cross spectrum (complex<br>
valued), and 10*log10(|Pxy|) is plotted<br>
Refs:<br>
Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)<br>
kwargs control the Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-disconnect"><strong>disconnect</strong></a>(self, cid)</dt><dd><tt>disconnect from the <a href="#Axes">Axes</a> event.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-draw_artist"><strong>draw_artist</strong></a>(self, a)</dt><dd><tt>This method can only be used after an initial draw which<br>
caches the renderer. It is used to efficiently update <a href="#Axes">Axes</a><br>
data (axis ticks, labels, etc are not updated)</tt></dd></dl>
<dl><dt><a name="PolarSubplot-errorbar"><strong>errorbar</strong></a>(self, x, y, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, fmt<font color="#909090">='b-'</font>, ecolor<font color="#909090">=None</font>, capsize<font color="#909090">=3</font>, barsabove<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>ERRORBAR(x, y, yerr=None, xerr=None,<br>
fmt='b-', ecolor=None, capsize=3, barsabove=False)<br>
Plot x versus y with error deltas in yerr and xerr.<br>
Vertical errorbars are plotted if yerr is not None<br>
Horizontal errorbars are plotted if xerr is not None<br>
xerr and yerr may be any of:<br>
a rank-0, Nx1 Numpy array - symmetric errorbars +/- value<br>
an N-element list or tuple - symmetric errorbars +/- value<br>
a rank-1, Nx2 Numpy array - asymmetric errorbars -column1/+column2<br>
Alternatively, x, y, xerr, and yerr can all be scalars, which<br>
plots a single error bar at x, y.<br>
fmt is the plot format symbol for y. if fmt is None, just<br>
plot the errorbars with no line symbols. This can be useful<br>
for creating a bar plot with errorbars<br>
ecolor is a matplotlib color arg which gives the color the<br>
errorbar lines; if None, use the marker color.<br>
capsize is the size of the error bar caps in points<br>
barsabove, if True, will plot the errorbars above the plot symbols<br>
- default is below<br>
kwargs are passed on to the plot command for the markers.<br>
So you can add additional key=value pairs to control the<br>
errorbar markers. For example, this code makes big red<br>
squares with thick green edges<br>
>>> x,y,yerr = rand(3,10)<br>
>>> <a href="#PolarSubplot-errorbar">errorbar</a>(x, y, yerr, marker='s',<br>
mfc='red', mec='green', ms=20, mew=4)<br>
mfc, mec, ms and mew are aliases for the longer property<br>
names, markerfacecolor, markeredgecolor, markersize and<br>
markeredgewith.<br>
valid kwargs for the marker properties are<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number<br>
Return value is a length 3 tuple. The first element is the<br>
Line2D instance for the y symbol lines. The second element is<br>
a list of error bar cap lines, the third element is a list of<br>
line collections for the horizontal and vertical error ranges</tt></dd></dl>
<dl><dt><a name="PolarSubplot-fill"><strong>fill</strong></a>(self, *args, **kwargs)</dt><dd><tt>FILL(*args, **kwargs)<br>
plot filled polygons. *args is a variable length argument, allowing<br>
for multiple x,y pairs with an optional color format string; see plot<br>
for details on the argument parsing. For example, all of the<br>
following are legal, assuming ax is an <a href="#Axes">Axes</a> instance:<br>
ax.<a href="#PolarSubplot-fill">fill</a>(x,y) # plot polygon with vertices at x,y<br>
ax.<a href="#PolarSubplot-fill">fill</a>(x,y, 'b' ) # plot polygon with vertices at x,y in blue<br>
An arbitrary number of x, y, color groups can be specified, as in<br>
ax.<a href="#PolarSubplot-fill">fill</a>(x1, y1, 'g', x2, y2, 'r')<br>
Return value is a list of patches that were added<br>
The same color strings that plot supports are supported by the fill<br>
format string.<br>
kwargs control the Polygon properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-format_xdata"><strong>format_xdata</strong></a>(self, x)</dt><dd><tt>Return x string formatted. This function will use the attribute<br>
self.<strong>fmt_xdata</strong> if it is callable, else will fall back on the xaxis<br>
major formatter</tt></dd></dl>
<dl><dt><a name="PolarSubplot-format_ydata"><strong>format_ydata</strong></a>(self, y)</dt><dd><tt>Return y string formatted. This function will use the attribute<br>
self.<strong>fmt_ydata</strong> if it is callable, else will fall back on the yaxis<br>
major formatter</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_adjustable"><strong>get_adjustable</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarSubplot-get_anchor"><strong>get_anchor</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarSubplot-get_aspect"><strong>get_aspect</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarSubplot-get_autoscale_on"><strong>get_autoscale_on</strong></a>(self)</dt><dd><tt>Get whether autoscaling is applied on plot commands</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_axis_bgcolor"><strong>get_axis_bgcolor</strong></a>(self)</dt><dd><tt>Return the axis background color</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_axisbelow"><strong>get_axisbelow</strong></a>(self)</dt><dd><tt>Get whether axist below is true or not</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_child_artists"><strong>get_child_artists</strong></a>(self)</dt><dd><tt>Return a list of artists the axes contains. Deprecated</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_cursor_props"><strong>get_cursor_props</strong></a>(self)</dt><dd><tt>return the cursor props as a linewidth, color tuple where<br>
linewidth is a float and color is an RGBA tuple</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_frame"><strong>get_frame</strong></a>(self)</dt><dd><tt>Return the axes Rectangle frame</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_frame_on"><strong>get_frame_on</strong></a>(self)</dt><dd><tt>Get whether the axes rectangle patch is drawn</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_images"><strong>get_images</strong></a>(self)</dt><dd><tt>return a list of <a href="#Axes">Axes</a> images contained by the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_legend"><strong>get_legend</strong></a>(self)</dt><dd><tt>Return the Legend instance, or None if no legend is defined</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_lines"><strong>get_lines</strong></a>(self)</dt><dd><tt>Return a list of lines contained by the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_navigate"><strong>get_navigate</strong></a>(self)</dt><dd><tt>Get whether the axes responds to navigation commands</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_navigate_mode"><strong>get_navigate_mode</strong></a>(self)</dt><dd><tt>Get the navigation toolbar button status: 'PAN', 'ZOOM', or None</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_position"><strong>get_position</strong></a>(self, original<font color="#909090">=False</font>)</dt><dd><tt>Return the axes rectangle left, bottom, width, height</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_renderer_cache"><strong>get_renderer_cache</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarSubplot-get_window_extent"><strong>get_window_extent</strong></a>(self, *args, **kwargs)</dt><dd><tt>get the axes bounding box in display space; args and kwargs are empty</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_xaxis"><strong>get_xaxis</strong></a>(self)</dt><dd><tt>Return the XAxis instance</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_xgridlines"><strong>get_xgridlines</strong></a>(self)</dt><dd><tt>Get the x grid lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_xlim"><strong>get_xlim</strong></a>(self)</dt><dd><tt>Get the x axis range [xmin, xmax]</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_xticklabels"><strong>get_xticklabels</strong></a>(self)</dt><dd><tt>Get the xtick labels as a list of Text instances</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_xticklines"><strong>get_xticklines</strong></a>(self)</dt><dd><tt>Get the xtick lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_xticks"><strong>get_xticks</strong></a>(self)</dt><dd><tt>Return the x ticks as a list of locations</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_yaxis"><strong>get_yaxis</strong></a>(self)</dt><dd><tt>Return the YAxis instance</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_ygridlines"><strong>get_ygridlines</strong></a>(self)</dt><dd><tt>Get the y grid lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_ylim"><strong>get_ylim</strong></a>(self)</dt><dd><tt>Get the y axis range [ymin, ymax]</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_yticklabels"><strong>get_yticklabels</strong></a>(self)</dt><dd><tt>Get the ytick labels as a list of Text instances</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_yticklines"><strong>get_yticklines</strong></a>(self)</dt><dd><tt>Get the ytick lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_yticks"><strong>get_yticks</strong></a>(self)</dt><dd><tt>Return the y ticks as a list of locations</tt></dd></dl>
<dl><dt><a name="PolarSubplot-hist"><strong>hist</strong></a>(self, x, bins<font color="#909090">=10</font>, normed<font color="#909090">=0</font>, bottom<font color="#909090">=None</font>, align<font color="#909090">='edge'</font>, orientation<font color="#909090">='vertical'</font>, width<font color="#909090">=None</font>, log<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>HIST(x, bins=10, normed=0, bottom=None,<br>
align='edge', orientation='vertical', width=None,<br>
log=False, **kwargs)<br>
Compute the histogram of x. bins is either an integer number of<br>
bins or a sequence giving the bins. x are the data to be binned.<br>
The return values is (n, bins, patches)<br>
If normed is true, the first element of the return tuple will<br>
be the counts normalized to form a probability density, ie,<br>
n/(len(x)*dbin). In a probability density, the integral of<br>
the histogram should be one (we assume equally spaced bins);<br>
you can verify that with<br>
# trapezoidal integration of the probability density function<br>
from matplotlib.mlab import trapz<br>
pdf, bins, patches = ax.<a href="#PolarSubplot-hist">hist</a>(...)<br>
print trapz(bins, pdf)<br>
align = 'edge' | 'center'. Interprets bins either as edge<br>
or center values<br>
orientation = 'horizontal' | 'vertical'. If horizontal, barh<br>
will be used and the "bottom" kwarg will be the left edges.<br>
width: the width of the bars. If None, automatically compute<br>
the width.<br>
log: if True, the histogram axis will be set to a log scale<br>
kwargs are used to update the properties of the<br>
hist Rectangles:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-hlines"><strong>hlines</strong></a>(self, y, xmin, xmax, colors<font color="#909090">='k'</font>, linestyle<font color="#909090">='solid'</font>, label<font color="#909090">=''</font>, **kwargs)</dt><dd><tt>HLINES(y, xmin, xmax, colors='k', linestyle='solid', **kwargs)<br>
plot horizontal lines at each y from xmin to xmax. xmin or xmax can<br>
be scalars or len(x) numpy arrays. If they are scalars, then the<br>
respective values are constant, else the widths of the lines are<br>
determined by xmin and xmax<br>
colors is a line collections color args, either a single color or a len(x) list of colors<br>
linestyle is one of solid|dashed|dashdot|dotted<br>
Returns the LineCollection that was added</tt></dd></dl>
<dl><dt><a name="PolarSubplot-hold"><strong>hold</strong></a>(self, b<font color="#909090">=None</font>)</dt><dd><tt>HOLD(b=None)<br>
<br>
Set the hold state. If hold is None (default), toggle the<br>
hold state. Else set the hold state to boolean value b.<br>
<br>
Eg<br>
<a href="#PolarSubplot-hold">hold</a>() # toggle hold<br>
<a href="#PolarSubplot-hold">hold</a>(True) # hold is on<br>
<a href="#PolarSubplot-hold">hold</a>(False) # hold is off<br>
<br>
<br>
When hold is True, subsequent plot commands will be added to<br>
the current axes. When hold is False, the current axes and<br>
figure will be cleared on the next plot command</tt></dd></dl>
<dl><dt><a name="PolarSubplot-imshow"><strong>imshow</strong></a>(self, X, cmap<font color="#909090">=None</font>, norm<font color="#909090">=None</font>, aspect<font color="#909090">=None</font>, interpolation<font color="#909090">=None</font>, alpha<font color="#909090">=1.0</font>, vmin<font color="#909090">=None</font>, vmax<font color="#909090">=None</font>, origin<font color="#909090">=None</font>, extent<font color="#909090">=None</font>, shape<font color="#909090">=None</font>, filternorm<font color="#909090">=1</font>, filterrad<font color="#909090">=4.0</font>, imlim<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>IMSHOW(X, cmap=None, norm=None, aspect=None, interpolation=None,<br>
alpha=1.0, vmin=None, vmax=None, origin=None, extent=None)<br>
<br>
IMSHOW(X) - plot image X to current axes, resampling to scale to axes<br>
size (X may be numarray/Numeric array or PIL image)<br>
<br>
IMSHOW(X, **kwargs) - Use keyword args to control image scaling,<br>
colormapping etc. See below for details<br>
<br>
<br>
Display the image in X to current axes. X may be a float array, a<br>
UInt8 array or a PIL image. If X is an array, X can have the following<br>
shapes:<br>
<br>
MxN : luminance (grayscale, float array only)<br>
<br>
MxNx3 : RGB (float or UInt8 array)<br>
<br>
MxNx4 : RGBA (float or UInt8 array)<br>
<br>
The value for each component of MxNx3 and MxNx4 float arrays should be<br>
in the range 0.0 to 1.0; MxN float arrays may be normalised.<br>
<br>
A matplotlib.image.AxesImage instance is returned<br>
<br>
The following kwargs are allowed:<br>
<br>
* cmap is a cm colormap instance, eg cm.jet. If None, default to rc<br>
image.cmap value (Ignored when X has RGB(A) information)<br>
<br>
* aspect is one of: auto, equal, or a number. If None, default to rc<br>
image.aspect value<br>
<br>
* interpolation is one of:<br>
<br>
'nearest', 'bilinear', 'bicubic', 'spline16', 'spline36',<br>
'hanning', 'hamming', 'hermite', 'kaiser', 'quadric',<br>
'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc',<br>
'lanczos', 'blackman'<br>
<br>
if interpolation is None, default to rc<br>
image.interpolation. See also th the filternorm and<br>
filterrad parameters<br>
<br>
* norm is a matplotlib.colors.Normalize instance; default is<br>
normalization(). This scales luminance -> 0-1 (only used for an<br>
MxN float array).<br>
<br>
* vmin and vmax are used to scale a luminance image to 0-1. If<br>
either is None, the min and max of the luminance values will be<br>
used. Note if you pass a norm instance, the settings for vmin and<br>
vmax will be ignored.<br>
<br>
* alpha = 1.0 : the alpha blending value<br>
<br>
* origin is 'upper' or 'lower', to place the [0,0]<br>
index of the array in the upper left or lower left corner of<br>
the axes. If None, default to rc image.origin<br>
<br>
* extent is (left, right, bottom, top) data values of the<br>
axes. The default assigns zero-based row, column indices<br>
to the x, y centers of the pixels.<br>
<br>
* shape is for raw buffer images<br>
<br>
* filternorm is a parameter for the antigrain image resize<br>
filter. From the antigrain documentation, if normalize=1,<br>
the filter normalizes integer values and corrects the<br>
rounding errors. It doesn't do anything with the source<br>
floating point values, it corrects only integers according<br>
to the rule of 1.0 which means that any sum of pixel<br>
weights must be equal to 1.0. So, the filter function<br>
must produce a graph of the proper shape.<br>
<br>
* filterrad: the filter radius for filters that have a radius<br>
parameter, ie when interpolation is one of: 'sinc',<br>
'lanczos' or 'blackman'<br>
<br>
Additional kwargs are matplotlib.artist properties</tt></dd></dl>
<dl><dt><a name="PolarSubplot-in_axes"><strong>in_axes</strong></a>(self, xwin, ywin)</dt><dd><tt>return True is the point xwin, ywin (display coords) are in the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="PolarSubplot-ishold"><strong>ishold</strong></a>(self)</dt><dd><tt>return the HOLD status of the axes</tt></dd></dl>
<dl><dt><a name="PolarSubplot-legend"><strong>legend</strong></a>(self, *args, **kwargs)</dt><dd><tt>LEGEND(*args, **kwargs)<br>
<br>
Place a legend on the current axes at location loc. Labels are a<br>
sequence of strings and loc can be a string or an integer specifying<br>
the legend location<br>
<br>
USAGE:<br>
<br>
Make a legend with existing lines<br>
<br>
>>> <a href="#PolarSubplot-legend">legend</a>()<br>
<br>
legend by itself will try and build a legend using the label<br>
property of the lines/patches/collections. You can set the label of<br>
a line by doing <a href="#PolarSubplot-plot">plot</a>(x, y, label='my data') or line.<a href="#PolarSubplot-set_label">set_label</a>('my<br>
data'). If label is set to '_nolegend_', the item will not be shown<br>
in legend.<br>
<br>
# automatically generate the legend from labels<br>
<a href="#PolarSubplot-legend">legend</a>( ('label1', 'label2', 'label3') )<br>
<br>
# Make a legend for a list of lines and labels<br>
<a href="#PolarSubplot-legend">legend</a>( (line1, line2, line3), ('label1', 'label2', 'label3') )<br>
<br>
# Make a legend at a given location, using a location argument<br>
# <a href="#PolarSubplot-legend">legend</a>( LABELS, LOC ) or<br>
# <a href="#PolarSubplot-legend">legend</a>( LINES, LABELS, LOC )<br>
<a href="#PolarSubplot-legend">legend</a>( ('label1', 'label2', 'label3'), loc='upper left')<br>
<a href="#PolarSubplot-legend">legend</a>( (line1, line2, line3), ('label1', 'label2', 'label3'), loc=2)<br>
<br>
The location codes are<br>
<br>
'best' : 0,<br>
'upper right' : 1, (default)<br>
'upper left' : 2,<br>
'lower left' : 3,<br>
'lower right' : 4,<br>
'right' : 5,<br>
'center left' : 6,<br>
'center right' : 7,<br>
'lower center' : 8,<br>
'upper center' : 9,<br>
'center' : 10,<br>
<br>
If none of these are suitable, loc can be a 2-tuple giving x,y<br>
in axes coords, ie,<br>
<br>
loc = 0, 1 is left top<br>
loc = 0.5, 0.5 is center, center<br>
<br>
and so on. The following kwargs are supported:<br>
<br>
isaxes=True # whether this is an axes legend<br>
numpoints = 4 # the number of points in the legend line<br>
prop = FontProperties(size='smaller') # the font property<br>
pad = 0.2 # the fractional whitespace inside the legend border<br>
markerscale = 0.6 # the relative size of legend markers vs. original<br>
shadow # if True, draw a shadow behind legend<br>
labelsep = 0.005 # the vertical space between the legend entries<br>
handlelen = 0.05 # the length of the legend lines<br>
handletextsep = 0.02 # the space between the legend line and legend text<br>
axespad = 0.02 # the border between the axes and legend edge</tt></dd></dl>
<dl><dt><a name="PolarSubplot-loglog"><strong>loglog</strong></a>(self, *args, **kwargs)</dt><dd><tt>LOGLOG(*args, **kwargs)<br>
Make a loglog plot with log scaling on the a and y axis. The args<br>
to semilog x are the same as the args to plot. See help plot for<br>
more info.<br>
Optional keyword args supported are any of the kwargs<br>
supported by plot or set_xscale or set_yscale. Notable, for<br>
log scaling:<br>
* basex: base of the x logarithm<br>
* subsx: the location of the minor ticks; None defaults to<br>
autosubs, which depend on the number of decades in the<br>
plot; see set_xscale for details<br>
* basey: base of the y logarithm<br>
* subsy: the location of the minor yticks; None defaults to<br>
autosubs, which depend on the number of decades in the<br>
plot; see set_yscale for details<br>
The remaining valid kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-matshow"><strong>matshow</strong></a>(self, Z, **kwargs)</dt><dd><tt>Plot a matrix as an image.<br>
<br>
The matrix will be shown the way it would be printed,<br>
with the first row at the top. Row and column numbering<br>
is zero-based.<br>
<br>
Argument:<br>
Z anything that can be interpreted as a 2-D array<br>
<br>
kwargs: all are passed to imshow. matshow sets defaults<br>
for extent, origin, interpolation, and aspect; use care<br>
in overriding the extent and origin kwargs, because they<br>
interact. (Also, if you want to change them, you probably<br>
should be using imshow directly in your own version of<br>
matshow.)<br>
<br>
Returns: an AxesImage instance</tt></dd></dl>
<dl><dt><a name="PolarSubplot-panx"><strong>panx</strong></a>(self, numsteps)</dt><dd><tt>Pan the x axis numsteps (plus pan right, minus pan left)</tt></dd></dl>
<dl><dt><a name="PolarSubplot-pany"><strong>pany</strong></a>(self, numsteps)</dt><dd><tt>Pan the x axis numsteps (plus pan up, minus pan down)</tt></dd></dl>
<dl><dt><a name="PolarSubplot-pcolor"><strong>pcolor</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#PolarSubplot-pcolor">pcolor</a>(*args, **kwargs): pseudocolor plot of a 2-D array<br>
Function signatures<br>
<a href="#PolarSubplot-pcolor">pcolor</a>(C, **kwargs)<br>
<a href="#PolarSubplot-pcolor">pcolor</a>(X, Y, C, **kwargs)<br>
C is the array of color values<br>
X and Y, if given, specify the (x,y) coordinates of the colored<br>
quadrilaterals; the quadrilateral for C[i,j] has corners at<br>
(X[i,j],Y[i,j]), (X[i,j+1],Y[i,j+1]), (X[i+1,j],Y[i+1,j]),<br>
(X[i+1,j+1],Y[i+1,j+1]). Ideally the dimensions of X and Y<br>
should be one greater than those of C; if the dimensions are the<br>
same, then the last row and column of C will be ignored.<br>
Note that the the column index corresponds to the x-coordinate,<br>
and the row index corresponds to y; for details, see<br>
the "Grid Orientation" section below.<br>
If either or both of X and Y are 1-D arrays or column vectors,<br>
they will be expanded as needed into the appropriate 2-D arrays,<br>
making a rectangular grid.<br>
X,Y and C may be masked arrays. If either C[i,j], or one<br>
of the vertices surrounding C[i,j] (X or Y at [i,j],[i+1,j],<br>
[i,j+1],[i=1,j+1]) is masked, nothing is plotted.<br>
Optional keyword args are shown with their defaults below (you must<br>
use kwargs for these):<br>
* cmap = cm.jet : a cm Colormap instance from matplotlib.cm.<br>
defaults to cm.jet<br>
* norm = Normalize() : matplotlib.colors.Normalize instance<br>
is used to scale luminance data to 0,1.<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used. If you pass a norm<br>
instance, vmin and vmax will be None<br>
* shading = 'flat' : or 'faceted'. If 'faceted', a black grid is<br>
drawn around each rectangle; if 'flat', edges are not drawn<br>
* alpha=1.0 : the alpha blending value<br>
Return value is a matplotlib.collections.PatchCollection<br>
object<br>
Grid Orientation<br>
The orientation follows the Matlab(TM) convention: an<br>
array C with shape (nrows, ncolumns) is plotted with<br>
the column number as X and the row number as Y, increasing<br>
up; hence it is plotted the way the array would be printed,<br>
except that the Y axis is reversed. That is, C is taken<br>
as C(y,x).<br>
Similarly for meshgrid:<br>
x = arange(5)<br>
y = arange(3)<br>
X, Y = meshgrid(x,y)<br>
is equivalent to<br>
X = array([[0, 1, 2, 3, 4],<br>
[0, 1, 2, 3, 4],<br>
[0, 1, 2, 3, 4]])<br>
Y = array([[0, 0, 0, 0, 0],<br>
[1, 1, 1, 1, 1],<br>
[2, 2, 2, 2, 2]])<br>
so if you have<br>
C = rand( len(x), len(y))<br>
then you need<br>
<a href="#PolarSubplot-pcolor">pcolor</a>(X, Y, transpose(C))<br>
or<br>
<a href="#PolarSubplot-pcolor">pcolor</a>(transpose(C))<br>
Dimensions<br>
Matlab pcolor always discards<br>
the last row and column of C, but matplotlib displays<br>
the last row and column if X and Y are not specified, or<br>
if X and Y have one more row and column than C.<br>
kwargs can be used to control the PolyCollection properties:<br>
alpha: float<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
edgecolor: matplotlib color arg or sequence of rgba tuples<br>
facecolor: matplotlib color arg or sequence of rgba tuples<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-pcolor_classic"><strong>pcolor_classic</strong></a>(self, *args)</dt><dd><tt>pcolor_classic is no longer available; please use pcolor,<br>
which is a drop-in replacement.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-pcolormesh"><strong>pcolormesh</strong></a>(self, *args, **kwargs)</dt><dd><tt>PCOLORMESH(*args, **kwargs)<br>
Function signatures<br>
PCOLORMESH(C) - make a pseudocolor plot of matrix C<br>
PCOLORMESH(X, Y, C) - a pseudo color plot of C on the matrices X and Y<br>
PCOLORMESH(C, **kwargs) - Use keyword args to control colormapping and<br>
scaling; see below<br>
C may be a masked array, but X and Y may not. Masked array support<br>
is implemented via cmap and norm; in contrast, pcolor simply does<br>
not draw quadrilaterals with masked colors or vertices.<br>
Optional keyword args are shown with their defaults below (you must<br>
use kwargs for these):<br>
* cmap = cm.jet : a cm Colormap instance from matplotlib.cm.<br>
defaults to cm.jet<br>
* norm = Normalize() : matplotlib.colors.Normalize instance<br>
is used to scale luminance data to 0,1. Instantiate it<br>
with clip=False if C is a masked array.<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used.<br>
* shading = 'flat' : or 'faceted'. If 'faceted', a black grid is<br>
drawn around each rectangle; if 'flat', edge colors are same as<br>
face colors<br>
* alpha=1.0 : the alpha blending value<br>
Return value is a matplotlib.collections.PatchCollection<br>
object<br>
See pcolor for an explantion of the grid orientation and the<br>
expansion of 1-D X and/or Y to 2-D arrays.<br>
kwargs can be used to control the QuadMesh polygon collection properties:<br>
alpha: float<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
edgecolor: matplotlib color arg or sequence of rgba tuples<br>
facecolor: matplotlib color arg or sequence of rgba tuples<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-pick"><strong>pick</strong></a>(self, *args)</dt><dd><tt><a href="#PolarSubplot-pick">pick</a>(mouseevent)<br>
<br>
each child artist will fire a pick event if mouseevent is over<br>
the artist and the artist has picker set</tt></dd></dl>
<dl><dt><a name="PolarSubplot-pie"><strong>pie</strong></a>(self, x, explode<font color="#909090">=None</font>, labels<font color="#909090">=None</font>, colors<font color="#909090">=None</font>, autopct<font color="#909090">=None</font>, pctdistance<font color="#909090">=0.59999999999999998</font>, shadow<font color="#909090">=False</font>)</dt><dd><tt>PIE(x, explode=None, labels=None,<br>
colors=('b', 'g', 'r', 'c', 'm', 'y', 'k', 'w'),<br>
autopct=None, pctdistance=0.6, shadow=False)<br>
<br>
Make a pie chart of array x. The fractional area of each wedge is<br>
given by x/sum(x). If sum(x)<=1, then the values of x give the<br>
fractional area directly and the array will not be normalized.<br>
<br>
- explode, if not None, is a len(x) array which specifies the<br>
fraction of the radius to offset that wedge.<br>
<br>
- colors is a sequence of matplotlib color args that the pie chart<br>
will cycle.<br>
<br>
- labels, if not None, is a len(x) list of labels.<br>
<br>
- autopct, if not None, is a string or function used to label the<br>
wedges with their numeric value. The label will be placed inside<br>
the wedge. If it is a format string, the label will be fmt%pct.<br>
If it is a function, it will be called<br>
<br>
- pctdistance is the ratio between the center of each pie slice<br>
and the start of the text generated by autopct. Ignored if autopct<br>
is None; default is 0.6.<br>
<br>
- shadow, if True, will draw a shadow beneath the pie.<br>
<br>
The pie chart will probably look best if the figure and axes are<br>
square. Eg,<br>
<br>
figure(figsize=(8,8))<br>
ax = axes([0.1, 0.1, 0.8, 0.8])<br>
<br>
Return value:<br>
<br>
If autopct is None, return a list of (patches, texts), where patches<br>
is a sequence of matplotlib.patches.Wedge instances and texts is a<br>
list of the label Text instnaces<br>
<br>
If autopct is not None, return (patches, texts, autotexts), where<br>
patches and texts are as above, and autotexts is a list of text<br>
instances for the numeric labels</tt></dd></dl>
<dl><dt><a name="PolarSubplot-plot"><strong>plot</strong></a>(self, *args, **kwargs)</dt><dd><tt>PLOT(*args, **kwargs)<br>
Plot lines and/or markers to the <a href="#Axes">Axes</a>. *args is a variable length<br>
argument, allowing for multiple x,y pairs with an optional format<br>
string. For example, each of the following is legal<br>
<a href="#PolarSubplot-plot">plot</a>(x,y) # plot x and y using the default line style and color<br>
<a href="#PolarSubplot-plot">plot</a>(x,y, 'bo') # plot x and y using blue circle markers<br>
<a href="#PolarSubplot-plot">plot</a>(y) # plot y using x as index array 0..N-1<br>
<a href="#PolarSubplot-plot">plot</a>(y, 'r+') # ditto, but with red plusses<br>
If x and/or y is 2-Dimensional, then the corresponding columns<br>
will be plotted.<br>
An arbitrary number of x, y, fmt groups can be specified, as in<br>
a.<a href="#PolarSubplot-plot">plot</a>(x1, y1, 'g^', x2, y2, 'g-')<br>
Return value is a list of lines that were added.<br>
The following line styles are supported:<br>
- : solid line<br>
-- : dashed line<br>
-. : dash-dot line<br>
: : dotted line<br>
. : points<br>
, : pixels<br>
o : circle symbols<br>
^ : triangle up symbols<br>
v : triangle down symbols<br>
< : triangle left symbols<br>
> : triangle right symbols<br>
s : square symbols<br>
+ : plus symbols<br>
x : cross symbols<br>
D : diamond symbols<br>
d : thin diamond symbols<br>
1 : tripod down symbols<br>
2 : tripod up symbols<br>
3 : tripod left symbols<br>
4 : tripod right symbols<br>
h : hexagon symbols<br>
H : rotated hexagon symbols<br>
p : pentagon symbols<br>
| : vertical line symbols<br>
_ : horizontal line symbols<br>
steps : use gnuplot style 'steps' # kwarg only<br>
The following color abbreviations are supported<br>
b : blue<br>
g : green<br>
r : red<br>
c : cyan<br>
m : magenta<br>
y : yellow<br>
k : black<br>
w : white<br>
In addition, you can specify colors in many weird and<br>
wonderful ways, including full names 'green', hex strings<br>
'#008000', RGB or RGBA tuples (0,1,0,1) or grayscale<br>
intensities as a string '0.8'.<br>
Line styles and colors are combined in a single format string, as in<br>
'bo' for blue circles.<br>
The **kwargs can be used to set line properties (any property that has<br>
a set_* method). You can use this to set a line label (for auto<br>
legends), linewidth, anitialising, marker face color, etc. Here is an<br>
example:<br>
<a href="#PolarSubplot-plot">plot</a>([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2)<br>
<a href="#PolarSubplot-plot">plot</a>([1,2,3], [1,4,9], 'rs', label='line 2')<br>
<a href="#PolarSubplot-axis">axis</a>([0, 4, 0, 10])<br>
<a href="#PolarSubplot-legend">legend</a>()<br>
If you make multiple lines with one plot command, the kwargs apply<br>
to all those lines, eg<br>
<a href="#PolarSubplot-plot">plot</a>(x1, y1, x2, y2, antialised=False)<br>
Neither line will be antialiased.<br>
The kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number<br>
kwargs scalex and scaley, if defined, are passed on<br>
to autoscale_view to determine whether the x and y axes are<br>
autoscaled; default True. See <a href="#Axes">Axes</a>.autoscale_view for more<br>
information</tt></dd></dl>
<dl><dt><a name="PolarSubplot-plot_date"><strong>plot_date</strong></a>(self, x, y, fmt<font color="#909090">='bo'</font>, tz<font color="#909090">=None</font>, xdate<font color="#909090">=True</font>, ydate<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>PLOT_DATE(x, y, fmt='bo', tz=None, xdate=True, ydate=False, **kwargs)<br>
Similar to the <a href="#PolarSubplot-plot">plot</a>() command, except the x or y (or both) data<br>
is considered to be dates, and the axis is labeled accordingly.<br>
x or y (or both) can be a sequence of dates represented as<br>
float days since 0001-01-01 UTC.<br>
fmt is a plot format string.<br>
tz is the time zone to use in labelling dates. Defaults to rc value.<br>
If xdate is True, the x-axis will be labeled with dates.<br>
If ydate is True, the y-axis will be labeled with dates.<br>
Note if you are using custom date tickers and formatters, it<br>
may be necessary to set the formatters/locators after the call<br>
to plot_date since plot_date will set the default tick locator<br>
to AutoDateLocator (if the tick locator is not already set to<br>
a DateLocator instance) and the default tick formatter to<br>
AutoDateFormatter (if the tick formatter is not already set to<br>
a DateFormatter instance).<br>
Valid kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number<br>
See matplotlib.dates for helper functions date2num, num2date<br>
and drange for help on creating the required floating point dates</tt></dd></dl>
<dl><dt><a name="PolarSubplot-psd"><strong>psd</strong></a>(self, x, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, window<font color="#909090">=<function window_hanning at 0xb5bc7764></font>, noverlap<font color="#909090">=0</font>, **kwargs)</dt><dd><tt>PSD(x, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0, **kwargs)<br>
The power spectral density by Welches average periodogram method. The<br>
vector x is divided into NFFT length segments. Each segment is<br>
detrended by function detrend and windowed by function window.<br>
noperlap gives the length of the overlap between segments. The<br>
absolute(fft(segment))**2 of each segment are averaged to compute Pxx,<br>
with a scaling to correct for power loss due to windowing. Fs is the<br>
sampling frequency.<br>
NFFT is the length of the fft segment; must be a power of 2<br>
Fs is the sampling frequency.<br>
detrend - the function applied to each segment before fft-ing,<br>
designed to remove the mean or linear trend. Unlike in matlab,<br>
where the detrend parameter is a vector, in matplotlib is it a<br>
function. The mlab module defines detrend_none, detrend_mean,<br>
detrend_linear, but you can use a custom function as well.<br>
window - the function used to window the segments. window is a<br>
function, unlike in matlab(TM) where it is a vector. mlab defines<br>
window_none, window_hanning, but you can use a custom function<br>
as well.<br>
noverlap gives the length of the overlap between segments.<br>
Returns the tuple Pxx, freqs<br>
For plotting, the power is plotted as 10*log10(pxx)) for decibels,<br>
though pxx itself is returned<br>
Refs:<br>
Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)<br>
kwargs control the Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-quiver"><strong>quiver</strong></a>(self, *args, **kw)</dt><dd><tt>Plot a 2-D field of arrows.<br>
<br>
Function signatures:<br>
<br>
<a href="#PolarSubplot-quiver">quiver</a>(U, V, **kw)<br>
<a href="#PolarSubplot-quiver">quiver</a>(U, V, C, **kw)<br>
<a href="#PolarSubplot-quiver">quiver</a>(X, Y, U, V, **kw)<br>
<a href="#PolarSubplot-quiver">quiver</a>(X, Y, U, V, C, **kw)<br>
<br>
Arguments:<br>
<br>
X, Y give the x and y coordinates of the arrow locations<br>
(default is tail of arrow; see 'pivot' kwarg)<br>
U, V give the x and y components of the arrow vectors<br>
C is an optional array used to map colors to the arrows<br>
<br>
All arguments may be 1-D or 2-D arrays or sequences.<br>
If X and Y are absent, they will be generated as a uniform grid.<br>
If U and V are 2-D arrays but X and Y are 1-D, and if<br>
len(X) and len(Y) match the column and row dimensions<br>
of U, then X and Y will be expanded with meshgrid.<br>
<br>
Keyword arguments (default given first):<br>
<br>
* units = 'width' | 'height' | 'dots' | 'inches' | 'x' | 'y'<br>
arrow units; the arrow dimensions *except for length*<br>
are in multiples of this unit.<br>
* scale = None | float<br>
data units per arrow unit, e.g. m/s per plot width;<br>
a smaller scale parameter makes the arrow longer.<br>
If None, a simple autoscaling algorithm is used, based<br>
on the average vector length and the number of vectors.<br>
<br>
Arrow dimensions and scales can be in any of several units:<br>
<br>
'width' or 'height': the width or height of the axes<br>
'dots' or 'inches': pixels or inches, based on the figure dpi<br>
'x' or 'y': X or Y data units<br>
<br>
In all cases the arrow aspect ratio is 1, so that if U==V the angle<br>
of the arrow on the plot is 45 degrees CCW from the X-axis.<br>
<br>
The arrows scale differently depending on the units, however.<br>
For 'x' or 'y', the arrows get larger as one zooms in; for other<br>
units, the arrow size is independent of the zoom state. For<br>
'width or 'height', the arrow size increases with the width and<br>
height of the axes, respectively, when the the window is resized;<br>
for 'dots' or 'inches', resizing does not change the arrows.<br>
<br>
<br>
* width = ? shaft width in arrow units; default depends on<br>
choice of units, above, and number of vectors;<br>
a typical starting value is about<br>
0.005 times the width of the plot.<br>
* headwidth = 3 head width as multiple of shaft width<br>
* headlength = 5 head length as multiple of shaft width<br>
* headaxislength = 4.5 head length at shaft intersection<br>
* minshaft = 1 length below which arrow scales, in units<br>
of head length. Do not set this to less<br>
than 1, or small arrows will look terrible!<br>
* minlength = 1 minimum length as a multiple of shaft width;<br>
if an arrow length is less than this, plot a<br>
dot (hexagon) of this diameter instead.<br>
<br>
The defaults give a slightly swept-back arrow; to make the<br>
head a triangle, make headaxislength the same as headlength.<br>
To make the arrow more pointed, reduce headwidth or increase<br>
headlength and headaxislength.<br>
To make the head smaller relative to the shaft, scale down<br>
all the head* parameters.<br>
You will probably do best to leave minshaft alone.<br>
<br>
* pivot = 'tail' | 'middle' | 'tip'<br>
The part of the arrow that is at the grid point; the arrow<br>
rotates about this point, hence the name 'pivot'.<br>
<br>
* color = 'k' | any matplotlib color spec or sequence of color specs.<br>
This is a synonym for the PolyCollection facecolor kwarg.<br>
If C has been set, 'color' has no effect.<br>
<br>
* All PolyCollection kwargs are valid, in the sense that they<br>
will be passed on to the PolyCollection constructor.<br>
In particular, one might want to use, for example:<br>
linewidths = (1,), edgecolors = ('g',)<br>
to make the arrows have green outlines of unit width.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-quiver2"><strong>quiver2</strong></a>(self, *args, **kw)</dt><dd><tt>Plot a 2-D field of arrows.<br>
<br>
Function signatures:<br>
<br>
<a href="#PolarSubplot-quiver">quiver</a>(U, V, **kw)<br>
<a href="#PolarSubplot-quiver">quiver</a>(U, V, C, **kw)<br>
<a href="#PolarSubplot-quiver">quiver</a>(X, Y, U, V, **kw)<br>
<a href="#PolarSubplot-quiver">quiver</a>(X, Y, U, V, C, **kw)<br>
<br>
Arguments:<br>
<br>
X, Y give the x and y coordinates of the arrow locations<br>
(default is tail of arrow; see 'pivot' kwarg)<br>
U, V give the x and y components of the arrow vectors<br>
C is an optional array used to map colors to the arrows<br>
<br>
All arguments may be 1-D or 2-D arrays or sequences.<br>
If X and Y are absent, they will be generated as a uniform grid.<br>
If U and V are 2-D arrays but X and Y are 1-D, and if<br>
len(X) and len(Y) match the column and row dimensions<br>
of U, then X and Y will be expanded with meshgrid.<br>
<br>
Keyword arguments (default given first):<br>
<br>
* units = 'width' | 'height' | 'dots' | 'inches' | 'x' | 'y'<br>
arrow units; the arrow dimensions *except for length*<br>
are in multiples of this unit.<br>
* scale = None | float<br>
data units per arrow unit, e.g. m/s per plot width;<br>
a smaller scale parameter makes the arrow longer.<br>
If None, a simple autoscaling algorithm is used, based<br>
on the average vector length and the number of vectors.<br>
<br>
Arrow dimensions and scales can be in any of several units:<br>
<br>
'width' or 'height': the width or height of the axes<br>
'dots' or 'inches': pixels or inches, based on the figure dpi<br>
'x' or 'y': X or Y data units<br>
<br>
In all cases the arrow aspect ratio is 1, so that if U==V the angle<br>
of the arrow on the plot is 45 degrees CCW from the X-axis.<br>
<br>
The arrows scale differently depending on the units, however.<br>
For 'x' or 'y', the arrows get larger as one zooms in; for other<br>
units, the arrow size is independent of the zoom state. For<br>
'width or 'height', the arrow size increases with the width and<br>
height of the axes, respectively, when the the window is resized;<br>
for 'dots' or 'inches', resizing does not change the arrows.<br>
<br>
<br>
* width = ? shaft width in arrow units; default depends on<br>
choice of units, above, and number of vectors;<br>
a typical starting value is about<br>
0.005 times the width of the plot.<br>
* headwidth = 3 head width as multiple of shaft width<br>
* headlength = 5 head length as multiple of shaft width<br>
* headaxislength = 4.5 head length at shaft intersection<br>
* minshaft = 1 length below which arrow scales, in units<br>
of head length. Do not set this to less<br>
than 1, or small arrows will look terrible!<br>
* minlength = 1 minimum length as a multiple of shaft width;<br>
if an arrow length is less than this, plot a<br>
dot (hexagon) of this diameter instead.<br>
<br>
The defaults give a slightly swept-back arrow; to make the<br>
head a triangle, make headaxislength the same as headlength.<br>
To make the arrow more pointed, reduce headwidth or increase<br>
headlength and headaxislength.<br>
To make the head smaller relative to the shaft, scale down<br>
all the head* parameters.<br>
You will probably do best to leave minshaft alone.<br>
<br>
* pivot = 'tail' | 'middle' | 'tip'<br>
The part of the arrow that is at the grid point; the arrow<br>
rotates about this point, hence the name 'pivot'.<br>
<br>
* color = 'k' | any matplotlib color spec or sequence of color specs.<br>
This is a synonym for the PolyCollection facecolor kwarg.<br>
If C has been set, 'color' has no effect.<br>
<br>
* All PolyCollection kwargs are valid, in the sense that they<br>
will be passed on to the PolyCollection constructor.<br>
In particular, one might want to use, for example:<br>
linewidths = (1,), edgecolors = ('g',)<br>
to make the arrows have green outlines of unit width.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-quiver_classic"><strong>quiver_classic</strong></a>(self, U, V, *args, **kwargs)</dt><dd><tt>QUIVER( X, Y, U, V )<br>
QUIVER( U, V )<br>
QUIVER( X, Y, U, V, S)<br>
QUIVER( U, V, S )<br>
QUIVER( ..., color=None, width=1.0, cmap=None, norm=None )<br>
<br>
Make a vector plot (U, V) with arrows on a grid (X, Y)<br>
<br>
If X and Y are not specified, U and V must be 2D arrays. Equally spaced<br>
X and Y grids are then generated using the meshgrid command.<br>
<br>
color can be a color value or an array of colors, so that the arrows can be<br>
colored according to another dataset. If cmap is specified and color is 'length',<br>
the colormap is used to give a color according to the vector's length.<br>
<br>
If color is a scalar field, the colormap is used to map the scalar to a color<br>
If a colormap is specified and color is an array of color triplets, then the<br>
colormap is ignored<br>
<br>
width is a scalar that controls the width of the arrows<br>
<br>
if S is specified it is used to scale the vectors. Use S=0 to disable automatic<br>
scaling.<br>
If S!=0, vectors are scaled to fit within the grid and then are multiplied by S.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-quiverkey"><strong>quiverkey</strong></a>(self, *args, **kw)</dt><dd><tt>Add a key to a quiver plot.<br>
<br>
Function signature:<br>
<a href="#PolarSubplot-quiverkey">quiverkey</a>(Q, X, Y, U, label, **kw)<br>
<br>
Arguments:<br>
Q is the Quiver instance returned by a call to quiver.<br>
X, Y give the location of the key; additional explanation follows.<br>
U is the length of the key<br>
label is a string with the length and units of the key<br>
<br>
Keyword arguments (default given first):<br>
* coordinates = 'axes' | 'figure' | 'data' | 'inches'<br>
Coordinate system and units for X, Y: 'axes' and 'figure'<br>
are normalized coordinate systems with 0,0 in the lower<br>
left and 1,1 in the upper right; 'data' are the axes<br>
data coordinates (used for the locations of the vectors<br>
in the quiver plot itself); 'inches' is position in the<br>
figure in inches, with 0,0 at the lower left corner.<br>
* color overrides face and edge colors from Q.<br>
* labelpos = 'N' | 'S' | 'E' | 'W'<br>
Position the label above, below, to the right, to the left<br>
of the arrow, respectively.<br>
* labelsep = 0.1 inches distance between the arrow and the label<br>
* labelcolor (defaults to default Text color)<br>
* fontproperties is a dictionary with keyword arguments accepted<br>
by the FontProperties initializer: family, style, variant,<br>
size, weight<br>
<br>
Any additional keyword arguments are used to override vector<br>
properties taken from Q.<br>
<br>
The positioning of the key depends on X, Y, coordinates, and<br>
labelpos. If labelpos is 'N' or 'S', X,Y give the position<br>
of the middle of the key arrow. If labelpos is 'E', X,Y<br>
positions the head, and if labelpos is 'W', X,Y positions the<br>
tail; in either of these two cases, X,Y is somewhere in the middle<br>
of the arrow+label key object.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-redraw_in_frame"><strong>redraw_in_frame</strong></a>(self)</dt><dd><tt>This method can only be used after an initial draw which<br>
caches the renderer. It is used to efficiently update <a href="#Axes">Axes</a><br>
data (axis ticks, labels, etc are not updated)</tt></dd></dl>
<dl><dt><a name="PolarSubplot-relim"><strong>relim</strong></a>(self)</dt><dd><tt>recompute the datalimits based on current artists</tt></dd></dl>
<dl><dt><a name="PolarSubplot-scatter"><strong>scatter</strong></a>(self, x, y, s<font color="#909090">=20</font>, c<font color="#909090">='b'</font>, marker<font color="#909090">='o'</font>, cmap<font color="#909090">=None</font>, norm<font color="#909090">=None</font>, vmin<font color="#909090">=None</font>, vmax<font color="#909090">=None</font>, alpha<font color="#909090">=1.0</font>, linewidths<font color="#909090">=None</font>, faceted<font color="#909090">=True</font>, verts<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SCATTER(x, y, s=20, c='b', marker='o', cmap=None, norm=None,<br>
vmin=None, vmax=None, alpha=1.0, linewidths=None,<br>
faceted=True, **kwargs)<br>
Supported function signatures:<br>
SCATTER(x, y, **kwargs)<br>
SCATTER(x, y, s, **kwargs)<br>
SCATTER(x, y, s, c, **kwargs)<br>
Make a scatter plot of x versus y, where x, y are 1-D sequences<br>
of the same length, N.<br>
Arguments s and c can also be given as kwargs; this is encouraged<br>
for readability.<br>
s is a size in points^2. It is a scalar<br>
or an array of the same length as x and y.<br>
c is a color and can be a single color format string,<br>
or a sequence of color specifications of length N,<br>
or a sequence of N numbers to be mapped to colors<br>
using the cmap and norm specified via kwargs (see below).<br>
Note that c should not be a single numeric RGB or RGBA<br>
sequence because that is indistinguishable from an array<br>
of values to be colormapped. c can be a 2-D array in which<br>
the rows are RGB or RGBA, however.<br>
The marker can be one of<br>
's' : square<br>
'o' : circle<br>
'^' : triangle up<br>
'>' : triangle right<br>
'v' : triangle down<br>
'<' : triangle left<br>
'd' : diamond<br>
'p' : pentagram<br>
'h' : hexagon<br>
'8' : octagon<br>
If marker is None and verts is not None, verts is a sequence<br>
of (x,y) vertices for a custom scatter symbol.<br>
s is a size argument in points squared.<br>
Any or all of x, y, s, and c may be masked arrays, in which<br>
case all masks will be combined and only unmasked points<br>
will be plotted.<br>
Other keyword args; the color mapping and normalization arguments will<br>
on be used if c is an array of floats<br>
* cmap = cm.jet : a colors.Colormap instance from matplotlib.cm.<br>
defaults to rc image.cmap<br>
* norm = Normalize() : matplotlib.colors.Normalize instance<br>
is used to scale luminance data to 0,1.<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used. Note if you pass a norm<br>
instance, your settings for vmin and vmax will be ignored<br>
* alpha =1.0 : the alpha value for the patches<br>
* linewidths, if None, defaults to (lines.linewidth,). Note<br>
that this is a tuple, and if you set the linewidths<br>
argument you must set it as a sequence of floats, as<br>
required by RegularPolyCollection -- see<br>
matplotlib.collections.RegularPolyCollection for details<br>
* faceted: if True, will use the default edgecolor for the<br>
markers. If False, will set the edgecolors to be the same<br>
as the facecolors<br>
Optional kwargs control the PatchCollection properties:<br>
alpha: float<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
edgecolor: matplotlib color arg or sequence of rgba tuples<br>
facecolor: matplotlib color arg or sequence of rgba tuples<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-scatter_classic"><strong>scatter_classic</strong></a>(self, x, y, s<font color="#909090">=None</font>, c<font color="#909090">='b'</font>)</dt><dd><tt>scatter_classic is no longer available; please use scatter.<br>
To help in porting, for comparison to the scatter docstring,<br>
here is the scatter_classic docstring:<br>
<br>
SCATTER_CLASSIC(x, y, s=None, c='b')<br>
<br>
Make a scatter plot of x versus y. s is a size (in data coords) and<br>
can be either a scalar or an array of the same length as x or y. c is<br>
a color and can be a single color format string or an length(x) array<br>
of intensities which will be mapped by the colormap jet.<br>
<br>
If size is None a default size will be used</tt></dd></dl>
<dl><dt><a name="PolarSubplot-semilogx"><strong>semilogx</strong></a>(self, *args, **kwargs)</dt><dd><tt>SEMILOGX(*args, **kwargs)<br>
Make a semilog plot with log scaling on the x axis. The args to<br>
semilog x are the same as the args to plot. See help plot for more<br>
info.<br>
Optional keyword args supported are any of the kwargs supported by<br>
plot or set_xscale. Notable, for log scaling:<br>
* basex: base of the logarithm<br>
* subsx: the location of the minor ticks; None defaults to<br>
autosubs, which depend on the number of decades in the<br>
plot; see set_xscale for details<br>
The remaining valid kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-semilogy"><strong>semilogy</strong></a>(self, *args, **kwargs)</dt><dd><tt>SEMILOGY(*args, **kwargs):<br>
Make a semilog plot with log scaling on the y axis. The args to<br>
semilogy are the same as the args to plot. See help plot for more<br>
info.<br>
Optional keyword args supported are any of the kwargs supported by<br>
plot or set_yscale. Notable, for log scaling:<br>
* basey: base of the logarithm<br>
* subsy: a sequence of the location of the minor ticks;<br>
None defaults to autosubs, which depend on the number of<br>
decades in the plot; see set_yscale for details<br>
The remaining valid kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_adjustable"><strong>set_adjustable</strong></a>(self, adjustable)</dt><dd><tt>ACCEPTS: ['box' | 'datalim']</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_anchor"><strong>set_anchor</strong></a>(self, anchor)</dt><dd><tt>ACCEPTS: ['C', 'SW', 'S', 'SE', 'E', 'NE', 'N', 'NW', 'W']</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_aspect"><strong>set_aspect</strong></a>(self, aspect, adjustable<font color="#909090">=None</font>, anchor<font color="#909090">=None</font>)</dt><dd><tt>aspect:<br>
'auto' - automatic; fill position rectangle with data<br>
'normal' - same as 'auto'; deprecated<br>
'equal' - same scaling from data to plot units for x and y<br>
num - a circle will be stretched such that the height<br>
is num times the width. aspect=1 is the same as<br>
aspect='equal'.<br>
<br>
adjustable:<br>
'box' - change physical size of axes<br>
'datalim' - change xlim or ylim<br>
<br>
anchor:<br>
'C' - centered<br>
'SW' - lower left corner<br>
'S' - middle of bottom edge<br>
'SE' - lower right corner<br>
etc.<br>
<br>
ACCEPTS: ['auto' | 'equal' | aspect_ratio]</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_autoscale_on"><strong>set_autoscale_on</strong></a>(self, b)</dt><dd><tt>Set whether autoscaling is applied on plot commands<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_axis_bgcolor"><strong>set_axis_bgcolor</strong></a>(self, color)</dt><dd><tt>set the axes background color<br>
<br>
ACCEPTS: any matplotlib color - see help(colors)</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_axis_off"><strong>set_axis_off</strong></a>(self)</dt><dd><tt>turn off the axis<br>
<br>
ACCEPTS: void</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_axis_on"><strong>set_axis_on</strong></a>(self)</dt><dd><tt>turn on the axis<br>
<br>
ACCEPTS: void</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_axisbelow"><strong>set_axisbelow</strong></a>(self, b)</dt><dd><tt>Set whether the axis ticks and gridlines are above or below most artists<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_cursor_props"><strong>set_cursor_props</strong></a>(self, *args)</dt><dd><tt>Set the cursor property as<br>
ax.<a href="#PolarSubplot-set_cursor_props">set_cursor_props</a>(linewidth, color) OR<br>
ax.<a href="#PolarSubplot-set_cursor_props">set_cursor_props</a>((linewidth, color))<br>
<br>
ACCEPTS: a (float, color) tuple</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_figure"><strong>set_figure</strong></a>(self, fig)</dt><dd><tt>Set the <a href="#Axes">Axes</a> figure<br>
<br>
ACCEPTS: a Figure instance</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_frame_on"><strong>set_frame_on</strong></a>(self, b)</dt><dd><tt>Set whether the axes rectangle patch is drawn<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_navigate"><strong>set_navigate</strong></a>(self, b)</dt><dd><tt>Set whether the axes responds to navigation toolbar commands<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_navigate_mode"><strong>set_navigate_mode</strong></a>(self, b)</dt><dd><tt>Set the navigation toolbar button status;<br>
this is not a user-API function.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_position"><strong>set_position</strong></a>(self, pos, which<font color="#909090">='both'</font>)</dt><dd><tt>Set the axes position with pos = [left, bottom, width, height]<br>
in relative 0,1 coords<br>
<br>
There are two position variables: one which is ultimately<br>
used, but which may be modified by apply_aspect, and a second<br>
which is the starting point for apply_aspect.<br>
<br>
which = 'active' to change the first;<br>
'original' to change the second;<br>
'both' to change both<br>
<br>
ACCEPTS: len(4) sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_title"><strong>set_title</strong></a>(self, label, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_TITLE(label, fontdict=None, **kwargs):<br>
Set the title for the axes. See the text docstring for information<br>
of how override and the optional args work<br>
kwargs are Text properties:<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_xscale"><strong>set_xscale</strong></a>(self, value, basex<font color="#909090">=10</font>, subsx<font color="#909090">=None</font>)</dt><dd><tt>SET_XSCALE(value, basex=10, subsx=None)<br>
<br>
Set the xscaling: 'log' or 'linear'<br>
<br>
If value is 'log', the additional kwargs have the following meaning<br>
<br>
* basex: base of the logarithm<br>
<br>
* subsx: a sequence of the location of the minor ticks;<br>
None defaults to autosubs, which depend on the number of<br>
decades in the plot. Eg for base 10, subsx=(1,2,5) will<br>
put minor ticks on 1,2,5,11,12,15,21, ....To turn off<br>
minor ticking, set subsx=[]<br>
<br>
ACCEPTS: ['log' | 'linear' ]</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_xticklabels"><strong>set_xticklabels</strong></a>(self, labels, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_XTICKLABELS(labels, fontdict=None, **kwargs)<br>
Set the xtick labels with list of strings labels Return a list of axis<br>
text instances.<br>
kwargs set the Text properties. Valid properties are<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: sequence of strings</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_xticks"><strong>set_xticks</strong></a>(self, ticks)</dt><dd><tt>Set the x ticks with list of ticks<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_yscale"><strong>set_yscale</strong></a>(self, value, basey<font color="#909090">=10</font>, subsy<font color="#909090">=None</font>)</dt><dd><tt>SET_YSCALE(value, basey=10, subsy=None)<br>
<br>
Set the yscaling: 'log' or 'linear'<br>
<br>
If value is 'log', the additional kwargs have the following meaning<br>
<br>
* basey: base of the logarithm<br>
<br>
* subsy: a sequence of the location of the minor ticks;<br>
None defaults to autosubs, which depend on the number of<br>
decades in the plot. Eg for base 10, subsy=(1,2,5) will<br>
put minor ticks on 1,2,5,11,12,15, 21, ....To turn off<br>
minor ticking, set subsy=[]<br>
<br>
ACCEPTS: ['log' | 'linear']</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_yticklabels"><strong>set_yticklabels</strong></a>(self, labels, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_YTICKLABELS(labels, fontdict=None, **kwargs)<br>
Set the ytick labels with list of strings labels. Return a list of<br>
Text instances.<br>
kwargs set Text properties for the labels. Valid properties are<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: sequence of strings</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_yticks"><strong>set_yticks</strong></a>(self, ticks)</dt><dd><tt>Set the y ticks with list of ticks<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="PolarSubplot-specgram"><strong>specgram</strong></a>(self, x, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, window<font color="#909090">=<function window_hanning at 0xb5bc7764></font>, noverlap<font color="#909090">=128</font>, cmap<font color="#909090">=None</font>, xextent<font color="#909090">=None</font>)</dt><dd><tt>SPECGRAM(x, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=128,<br>
cmap=None, xextent=None)<br>
<br>
Compute a spectrogram of data in x. Data are split into NFFT length<br>
segements and the PSD of each section is computed. The windowing<br>
function window is applied to each segment, and the amount of overlap<br>
of each segment is specified with noverlap.<br>
<br>
* cmap is a colormap; if None use default determined by rc<br>
<br>
* xextent is the image extent in the xaxes xextent=xmin, xmax -<br>
default 0, max(bins), 0, max(freqs) where bins is the return<br>
value from matplotlib.matplotlib.mlab.specgram<br>
<br>
* See help(psd) for information on the other keyword arguments.<br>
<br>
Return value is (Pxx, freqs, bins, im), where<br>
<br>
bins are the time points the spectrogram is calculated over<br>
<br>
freqs is an array of frequencies<br>
<br>
Pxx is a len(times) x len(freqs) array of power<br>
<br>
im is a matplotlib.image.AxesImage.<br>
<br>
Note: If x is real (i.e. non-complex) only the positive spectrum is<br>
shown. If x is complex both positive and negative parts of the<br>
spectrum are shown.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-spy"><strong>spy</strong></a>(self, Z, precision<font color="#909090">=None</font>, marker<font color="#909090">=None</font>, markersize<font color="#909090">=None</font>, aspect<font color="#909090">='equal'</font>, **kwargs)</dt><dd><tt><a href="#PolarSubplot-spy">spy</a>(Z) plots the sparsity pattern of the 2-D array Z<br>
<br>
If precision is None, any non-zero value will be plotted;<br>
else, values of absolute(Z)>precision will be plotted.<br>
<br>
The array will be plotted as it would be printed, with<br>
the first index (row) increasing down and the second<br>
index (column) increasing to the right.<br>
<br>
By default aspect is 'equal' so that each array element<br>
occupies a square space; set the aspect kwarg to 'auto'<br>
to allow the plot to fill the plot box, or to any scalar<br>
number to specify the aspect ratio of an array element<br>
directly.<br>
<br>
Two plotting styles are available: image or marker. Both<br>
are available for full arrays, but only the marker style<br>
works for scipy.sparse.spmatrix instances.<br>
<br>
If marker and markersize are None, an image will be<br>
returned and any remaining kwargs are passed to imshow;<br>
else, a Line2D object will be returned with the value<br>
of marker determining the marker type, and any remaining<br>
kwargs passed to the axes plot method.<br>
<br>
If marker and markersize are None, useful kwargs include:<br>
cmap<br>
alpha<br>
See documentation for <a href="#PolarSubplot-imshow">imshow</a>() for details.<br>
For controlling colors, e.g. cyan background and red marks, use:<br>
cmap = matplotlib.colors.ListedColormap(['c','r'])<br>
<br>
If marker or markersize is not None, useful kwargs include:<br>
marker<br>
markersize<br>
color<br>
See documentation for <a href="#PolarSubplot-plot">plot</a>() for details.<br>
<br>
Useful values for marker include:<br>
's' square (default)<br>
'o' circle<br>
'.' point<br>
',' pixel</tt></dd></dl>
<dl><dt><a name="PolarSubplot-stem"><strong>stem</strong></a>(self, x, y, linefmt<font color="#909090">='b-'</font>, markerfmt<font color="#909090">='bo'</font>, basefmt<font color="#909090">='r-'</font>)</dt><dd><tt>STEM(x, y, linefmt='b-', markerfmt='bo', basefmt='r-')<br>
<br>
A stem plot plots vertical lines (using linefmt) at each x location<br>
from the baseline to y, and places a marker there using markerfmt. A<br>
horizontal line at 0 is is plotted using basefmt<br>
<br>
Return value is (markerline, stemlines, baseline) .<br>
<br>
See<br>
<a href="http://www.mathworks.com/access/helpdesk/help/techdoc/ref/stem.html">http://www.mathworks.com/access/helpdesk/help/techdoc/ref/stem.html</a><br>
for details and examples/stem_plot.py for a demo.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-text"><strong>text</strong></a>(self, x, y, s, fontdict<font color="#909090">=None</font>, withdash<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>TEXT(x, y, s, fontdict=None, **kwargs)<br>
Add text in string s to axis at location x,y (data coords)<br>
fontdict is a dictionary to override the default text properties.<br>
If fontdict is None, the defaults are determined by your rc<br>
parameters.<br>
withdash=True will create a TextWithDash instance instead<br>
of a Text instance.<br>
Individual keyword arguments can be used to override any given<br>
parameter<br>
<a href="#PolarSubplot-text">text</a>(x, y, s, fontsize=12)<br>
The default transform specifies that text is in data coords,<br>
alternatively, you can specify text in axis coords (0,0 lower left and<br>
1,1 upper right). The example below places text in the center of the<br>
axes<br>
<a href="#PolarSubplot-text">text</a>(0.5, 0.5,'matplotlib',<br>
horizontalalignment='center',<br>
verticalalignment='center',<br>
transform = ax.transAxes,<br>
)<br>
You can put a rectangular box around the text instance (eg to<br>
set a background color) by using the keyword bbox. bbox is a<br>
dictionary of matplotlib.patches.Rectangle properties (see help<br>
for Rectangle for a list of these). For example<br>
<a href="#PolarSubplot-text">text</a>(x, y, s, bbox=dict(facecolor='red', alpha=0.5))<br>
Valid kwargs are Text properties<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-ticklabel_format"><strong>ticklabel_format</strong></a>(self, **kwargs)</dt><dd><tt>Convenience method for manipulating the ScalarFormatter<br>
used by default for linear axes.<br>
<br>
kwargs:<br>
style = 'sci' (or 'scientific') or 'plain';<br>
plain turns off scientific notation<br>
axis = 'x', 'y', or 'both'<br>
<br>
Only the major ticks are affected.<br>
If the method is called when the ScalarFormatter is not<br>
the one being used, an AttributeError will be raised with<br>
no additional error message.<br>
<br>
Additional capabilities and/or friendlier error checking may be added.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-update_datalim"><strong>update_datalim</strong></a>(self, xys)</dt><dd><tt>Update the data lim bbox with seq of xy tups or equiv. 2-D array</tt></dd></dl>
<dl><dt><a name="PolarSubplot-update_datalim_numerix"><strong>update_datalim_numerix</strong></a>(self, x, y)</dt><dd><tt>Update the data lim bbox with seq of xy tups</tt></dd></dl>
<dl><dt><a name="PolarSubplot-vlines"><strong>vlines</strong></a>(self, x, ymin, ymax, colors<font color="#909090">='k'</font>, linestyle<font color="#909090">='solid'</font>, label<font color="#909090">=''</font>, **kwargs)</dt><dd><tt>VLINES(x, ymin, ymax, color='k')<br>
Plot vertical lines at each x from ymin to ymax. ymin or ymax can be<br>
scalars or len(x) numpy arrays. If they are scalars, then the<br>
respective values are constant, else the heights of the lines are<br>
determined by ymin and ymax<br>
colors is a line collections color args, either a single color<br>
or a len(x) list of colors<br>
linestyle is one of solid|dashed|dashdot|dotted<br>
Returns the LineCollection that was added<br>
kwargs are LineCollection properties:<br>
alpha: float or sequence of floats<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle: ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
segments: unknown<br>
transform: a matplotlib.transform transformation instance<br>
verts: unknown<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-xaxis_date"><strong>xaxis_date</strong></a>(self, tz<font color="#909090">=None</font>)</dt><dd><tt>Sets up x-axis ticks and labels that treat the x data as dates.<br>
<br>
tz is the time zone to use in labeling dates. Defaults to rc value.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-xcorr"><strong>xcorr</strong></a>(self, x, y, normed<font color="#909090">=False</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, usevlines<font color="#909090">=False</font>, maxlags<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>XCORR(x, y, normed=False, detrend=detrend_none, usevlines=False, **kwargs):<br>
Plot the cross correlation between x and y. If normed=True,<br>
normalize the data but the cross correlation at 0-th lag. x<br>
and y are detrended by the detrend callable (default no<br>
normalization. x and y must be equal length<br>
data are plotted as <a href="#PolarSubplot-plot">plot</a>(lags, c, **kwargs)<br>
return value is lags, c, line where lags are a length<br>
2*maxlags+1 lag vector, c is the 2*maxlags+1 auto correlation<br>
vector, and line is a Line2D instance returned by plot. The<br>
default linestyle is None and the default marker is 'o',<br>
though these can be overridden with keyword args. The cross<br>
correlation is performed with numerix cross_correlate with<br>
mode=2.<br>
If usevlines is True, <a href="#Axes">Axes</a>.vlines rather than <a href="#Axes">Axes</a>.plot is used<br>
to draw vertical lines from the origin to the acorr.<br>
Otherwise the plotstyle is determined by the kwargs, which are<br>
Line2D properties. If usevlines, the return value is lags, c,<br>
linecol, b where linecol is the LineCollection and b is the x-axis<br>
if usevlines=True, kwargs are passed onto <a href="#Axes">Axes</a>.vlines<br>
if usevlines=False, kwargs are passed onto <a href="#Axes">Axes</a>.plot<br>
maxlags is a positive integer detailing the number of lags to show.<br>
The default value of None will return all (2*len(x)-1) lags.<br>
See the respective function for documentation on valid kwargs</tt></dd></dl>
<dl><dt><a name="PolarSubplot-yaxis_date"><strong>yaxis_date</strong></a>(self, tz<font color="#909090">=None</font>)</dt><dd><tt>Sets up y-axis ticks and labels that treat the y data as dates.<br>
<br>
tz is the time zone to use in labeling dates. Defaults to rc value.</tt></dd></dl>
<dl><dt><a name="PolarSubplot-zoomx"><strong>zoomx</strong></a>(self, numsteps)</dt><dd><tt>Zoom in on the x xaxis numsteps (plus for zoom in, minus for zoom out)</tt></dd></dl>
<dl><dt><a name="PolarSubplot-zoomy"><strong>zoomy</strong></a>(self, numsteps)</dt><dd><tt>Zoom in on the x xaxis numsteps (plus for zoom in, minus for zoom out)</tt></dd></dl>
<hr>
Data and other attributes inherited from <a href="matplotlib.axes.html#Axes">Axes</a>:<br>
<dl><dt><strong>scaled</strong> = {0: 'linear', 1: 'log'}</dl>
<hr>
Methods inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><a name="PolarSubplot-add_callback"><strong>add_callback</strong></a>(self, func)</dt></dl>
<dl><dt><a name="PolarSubplot-convert_xunits"><strong>convert_xunits</strong></a>(self, x)</dt><dd><tt>for artists in an axes, if the xaxis as units support,<br>
convert x using xaxis unit type</tt></dd></dl>
<dl><dt><a name="PolarSubplot-convert_yunits"><strong>convert_yunits</strong></a>(self, y)</dt><dd><tt>for artists in an axes, if the yaxis as units support,<br>
convert y using yaxis unit type</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_alpha"><strong>get_alpha</strong></a>(self)</dt><dd><tt>Return the alpha value used for blending - not supported on all<br>
backends</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_animated"><strong>get_animated</strong></a>(self)</dt><dd><tt>return the artist's animated state</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_axes"><strong>get_axes</strong></a>(self)</dt><dd><tt>return the axes instance the artist resides in, or None</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_clip_box"><strong>get_clip_box</strong></a>(self)</dt><dd><tt>Return artist clipbox</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_clip_on"><strong>get_clip_on</strong></a>(self)</dt><dd><tt>Return whether artist uses clipping</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_clip_path"><strong>get_clip_path</strong></a>(self)</dt><dd><tt>Return artist clip path</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_figure"><strong>get_figure</strong></a>(self)</dt><dd><tt>return the figure instance</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_label"><strong>get_label</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarSubplot-get_picker"><strong>get_picker</strong></a>(self)</dt><dd><tt>return the Pickeration instance used by this artist</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_transform"><strong>get_transform</strong></a>(self)</dt><dd><tt>return the Transformation instance used by this artist</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_visible"><strong>get_visible</strong></a>(self)</dt><dd><tt>return the artist's visiblity</tt></dd></dl>
<dl><dt><a name="PolarSubplot-get_zorder"><strong>get_zorder</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarSubplot-have_units"><strong>have_units</strong></a>(self)</dt><dd><tt>return True if units are set on the x or y axes</tt></dd></dl>
<dl><dt><a name="PolarSubplot-is_figure_set"><strong>is_figure_set</strong></a>(self)</dt></dl>
<dl><dt><a name="PolarSubplot-is_transform_set"><strong>is_transform_set</strong></a>(self)</dt><dd><tt><a href="matplotlib.artist.html#Artist">Artist</a> has transform explicity let</tt></dd></dl>
<dl><dt><a name="PolarSubplot-pchanged"><strong>pchanged</strong></a>(self)</dt><dd><tt>fire event when property changed</tt></dd></dl>
<dl><dt><a name="PolarSubplot-pickable"><strong>pickable</strong></a>(self)</dt><dd><tt>return True if self is pickable</tt></dd></dl>
<dl><dt><a name="PolarSubplot-remove_callback"><strong>remove_callback</strong></a>(self, oid)</dt></dl>
<dl><dt><a name="PolarSubplot-set"><strong>set</strong></a>(self, **kwargs)</dt><dd><tt>A tkstyle set command, pass kwargs to set properties</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_alpha"><strong>set_alpha</strong></a>(self, alpha)</dt><dd><tt>Set the alpha value used for blending - not supported on<br>
all backends<br>
<br>
ACCEPTS: float</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_animated"><strong>set_animated</strong></a>(self, b)</dt><dd><tt>set the artist's animation state<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_axes"><strong>set_axes</strong></a>(self, axes)</dt><dd><tt>set the axes instance the artist resides in, if any<br>
<br>
ACCEPTS: an axes instance</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_clip_box"><strong>set_clip_box</strong></a>(self, clipbox)</dt><dd><tt>Set the artist's clip Bbox<br>
<br>
ACCEPTS: a matplotlib.transform.Bbox instance</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_clip_on"><strong>set_clip_on</strong></a>(self, b)</dt><dd><tt>Set whether artist uses clipping<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_clip_path"><strong>set_clip_path</strong></a>(self, path)</dt><dd><tt>Set the artist's clip path<br>
<br>
ACCEPTS: an agg.path_storage instance</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_label"><strong>set_label</strong></a>(self, s)</dt><dd><tt>Set the line label to s for auto legend<br>
<br>
ACCEPTS: any string</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_lod"><strong>set_lod</strong></a>(self, on)</dt><dd><tt>Set Level of Detail on or off. If on, the artists may examine<br>
things like the pixel width of the axes and draw a subset of<br>
their contents accordingly<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_picker"><strong>set_picker</strong></a>(self, picker)</dt><dd><tt>set the epsilon for picking used by this artist<br>
<br>
picker can be one of the following:<br>
<br>
None - picking is disabled for this artist (default)<br>
<br>
boolean - if True then picking will be enabled and the<br>
artist will fire a pick event if the mouse event is over<br>
the artist<br>
<br>
float - if picker is a number it is interpreted as an<br>
epsilon tolerance in points and the the artist will fire<br>
off an event if it's data is within epsilon of the mouse<br>
event. For some artists like lines and patch collections,<br>
the artist may provide additional data to the pick event<br>
that is generated, eg the indices of the data within<br>
epsilon of the pick event<br>
<br>
function - if picker is callable, it is a user supplied<br>
function which determines whether the artist is hit by the<br>
mouse event.<br>
<br>
hit, props = picker(artist, mouseevent)<br>
<br>
to determine the hit test. if the mouse event is over the<br>
artist, return hit=True and props is a dictionary of<br>
properties you want added to the PickEvent attributes<br>
<br>
ACCEPTS: [None|float|boolean|callable]</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_transform"><strong>set_transform</strong></a>(self, t)</dt><dd><tt>set the Transformation instance used by this artist<br>
<br>
ACCEPTS: a matplotlib.transform transformation instance</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_visible"><strong>set_visible</strong></a>(self, b)</dt><dd><tt>set the artist's visiblity<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="PolarSubplot-set_zorder"><strong>set_zorder</strong></a>(self, level)</dt><dd><tt>Set the zorder for the artist<br>
<br>
ACCEPTS: any number</tt></dd></dl>
<dl><dt><a name="PolarSubplot-update"><strong>update</strong></a>(self, props)</dt></dl>
<dl><dt><a name="PolarSubplot-update_from"><strong>update_from</strong></a>(self, other)</dt><dd><tt>copy properties from other to self</tt></dd></dl>
<hr>
Data and other attributes inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><strong>aname</strong> = 'Artist'</dl>
<dl><dt><strong>zorder</strong> = 0</dl>
</td></tr></table> <p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#ffc8d8">
<td colspan=3 valign=bottom> <br>
<font color="#000000" face="helvetica, arial"><a name="Subplot">class <strong>Subplot</strong></a>(<a href="matplotlib.axes.html#SubplotBase">SubplotBase</a>, <a href="matplotlib.axes.html#Axes">Axes</a>)</font></td></tr>
<tr bgcolor="#ffc8d8"><td rowspan=2><tt> </tt></td>
<td colspan=2><tt>Emulate matlab's(TM) subplot command, creating axes with<br>
<br>
<a href="#Subplot">Subplot</a>(numRows, numCols, plotNum)<br>
<br>
where plotNum=1 is the first plot number and increasing plotNums<br>
fill rows first. max(plotNum)==numRows*numCols<br>
<br>
You can leave out the commas if numRows<=numCols<=plotNum<10, as<br>
in<br>
<br>
<a href="#Subplot">Subplot</a>(211) # 2 rows, 1 column, first (upper) plot<br> </tt></td></tr>
<tr><td> </td>
<td width="100%"><dl><dt>Method resolution order:</dt>
<dd><a href="matplotlib.axes.html#Subplot">Subplot</a></dd>
<dd><a href="matplotlib.axes.html#SubplotBase">SubplotBase</a></dd>
<dd><a href="matplotlib.axes.html#Axes">Axes</a></dd>
<dd><a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a></dd>
</dl>
<hr>
Methods defined here:<br>
<dl><dt><a name="Subplot-__init__"><strong>__init__</strong></a>(self, fig, *args, **kwargs)</dt><dd><tt>See <a href="#Axes">Axes</a> base class documentation for args and kwargs</tt></dd></dl>
<hr>
Methods inherited from <a href="matplotlib.axes.html#SubplotBase">SubplotBase</a>:<br>
<dl><dt><a name="Subplot-change_geometry"><strong>change_geometry</strong></a>(self, numrows, numcols, num)</dt><dd><tt>change subplot geometry, eg from 1,1,1 to 2,2,3</tt></dd></dl>
<dl><dt><a name="Subplot-get_geometry"><strong>get_geometry</strong></a>(self)</dt><dd><tt>get the subplot geometry, eg 2,2,3</tt></dd></dl>
<dl><dt><a name="Subplot-is_first_col"><strong>is_first_col</strong></a>(self)</dt></dl>
<dl><dt><a name="Subplot-is_first_row"><strong>is_first_row</strong></a>(self)</dt></dl>
<dl><dt><a name="Subplot-is_last_col"><strong>is_last_col</strong></a>(self)</dt></dl>
<dl><dt><a name="Subplot-is_last_row"><strong>is_last_row</strong></a>(self)</dt></dl>
<dl><dt><a name="Subplot-label_outer"><strong>label_outer</strong></a>(self)</dt><dd><tt>set the visible property on ticklabels so xticklabels are<br>
visible only if the subplot is in the last row and yticklabels<br>
are visible only if the subplot is in the first column</tt></dd></dl>
<dl><dt><a name="Subplot-update_params"><strong>update_params</strong></a>(self)</dt><dd><tt>update the subplot position from fig.subplotpars</tt></dd></dl>
<hr>
Methods inherited from <a href="matplotlib.axes.html#Axes">Axes</a>:<br>
<dl><dt><a name="Subplot-acorr"><strong>acorr</strong></a>(self, x, **kwargs)</dt><dd><tt>ACORR(x, normed=False, detrend=detrend_none, usevlines=False,<br>
maxlags=None, **kwargs)<br>
Plot the autocorrelation of x. If normed=True, normalize the<br>
data but the autocorrelation at 0-th lag. x is detrended by<br>
the detrend callable (default no normalization.<br>
data are plotted as <a href="#Subplot-plot">plot</a>(lags, c, **kwargs)<br>
return value is lags, c, line where lags are a length<br>
2*maxlags+1 lag vector, c is the 2*maxlags+1 auto correlation<br>
vector, and line is a Line2D instance returned by plot. The<br>
default linestyle is None and the default marker is 'o',<br>
though these can be overridden with keyword args. The cross<br>
correlation is performed with numerix cross_correlate with<br>
mode=2.<br>
If usevlines is True, <a href="#Axes">Axes</a>.vlines rather than <a href="#Axes">Axes</a>.plot is used<br>
to draw vertical lines from the origin to the acorr.<br>
Otherwise the plotstyle is determined by the kwargs, which are<br>
Line2D properties. If usevlines, the return value is lags, c,<br>
linecol, b where linecol is the LineCollection and b is the x-axis<br>
if usevlines=True, kwargs are passed onto <a href="#Axes">Axes</a>.vlines<br>
if usevlines=False, kwargs are passed onto <a href="#Axes">Axes</a>.plot<br>
maxlags is a positive integer detailing the number of lags to show.<br>
The default value of None will return all (2*len(x)-1) lags.<br>
See the respective function for documentation on valid kwargs</tt></dd></dl>
<dl><dt><a name="Subplot-add_artist"><strong>add_artist</strong></a>(self, a)</dt><dd><tt>Add any artist to the axes</tt></dd></dl>
<dl><dt><a name="Subplot-add_collection"><strong>add_collection</strong></a>(self, collection, autolim<font color="#909090">=False</font>)</dt><dd><tt>add a Collection instance to <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="Subplot-add_line"><strong>add_line</strong></a>(self, line)</dt><dd><tt>Add a line to the list of plot lines</tt></dd></dl>
<dl><dt><a name="Subplot-add_patch"><strong>add_patch</strong></a>(self, p)</dt><dd><tt>Add a patch to the list of <a href="#Axes">Axes</a> patches; the clipbox will be<br>
set to the <a href="#Axes">Axes</a> clipping box. If the transform is not set, it<br>
wil be set to self.<strong>transData</strong>.</tt></dd></dl>
<dl><dt><a name="Subplot-add_table"><strong>add_table</strong></a>(self, tab)</dt><dd><tt>Add a table instance to the list of axes tables</tt></dd></dl>
<dl><dt><a name="Subplot-annotate"><strong>annotate</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#Subplot-annotate">annotate</a>(self, s, xy, textloc,<br>
xycoords='data', textcoords='data',<br>
lineprops=None,<br>
markerprops=None<br>
**props)<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-apply_aspect"><strong>apply_aspect</strong></a>(self, data_ratio<font color="#909090">=None</font>)</dt><dd><tt>Use self.<strong>_aspect</strong> and self.<strong>_adjustable</strong> to modify the<br>
axes box or the view limits.<br>
The data_ratio kwarg is set to 1 for polar axes. It is<br>
used only when _adjustable is 'box'.</tt></dd></dl>
<dl><dt><a name="Subplot-arrow"><strong>arrow</strong></a>(self, x, y, dx, dy, **kwargs)</dt><dd><tt>Draws arrow on specified axis from (x,y) to (x+dx,y+dy).<br>
Optional kwargs control the arrow properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-autoscale_view"><strong>autoscale_view</strong></a>(self, tight<font color="#909090">=False</font>, scalex<font color="#909090">=True</font>, scaley<font color="#909090">=True</font>)</dt><dd><tt>autoscale the view limits using the data limits. You can<br>
selectively autoscale only a single axis, eg, the xaxis by<br>
setting scaley to False. The autoscaling preserves any<br>
axis direction reversal that has already been done.</tt></dd></dl>
<dl><dt><a name="Subplot-axhline"><strong>axhline</strong></a>(self, y<font color="#909090">=0</font>, xmin<font color="#909090">=0</font>, xmax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXHLINE(y=0, xmin=0, xmax=1, **kwargs)<br>
Axis Horizontal Line<br>
Draw a horizontal line at y from xmin to xmax. With the default<br>
values of xmin=0 and xmax=1, this line will always span the horizontal<br>
extent of the axes, regardless of the xlim settings, even if you<br>
change them, eg with the xlim command. That is, the horizontal extent<br>
is in axes coords: 0=left, 0.5=middle, 1.0=right but the y location is<br>
in data coordinates.<br>
Return value is the Line2D instance. kwargs are the same as kwargs to<br>
plot, and can be used to control the line properties. Eg<br>
# draw a thick red hline at y=0 that spans the xrange<br>
<a href="#Subplot-axhline">axhline</a>(linewidth=4, color='r')<br>
# draw a default hline at y=1 that spans the xrange<br>
<a href="#Subplot-axhline">axhline</a>(y=1)<br>
# draw a default hline at y=.5 that spans the the middle half of<br>
# the xrange<br>
<a href="#Subplot-axhline">axhline</a>(y=.5, xmin=0.25, xmax=0.75)<br>
Valid kwargs are Line2D properties<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-axhspan"><strong>axhspan</strong></a>(self, ymin, ymax, xmin<font color="#909090">=0</font>, xmax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXHSPAN(ymin, ymax, xmin=0, xmax=1, **kwargs)<br>
Axis Horizontal Span. ycoords are in data units and x<br>
coords are in axes (relative 0-1) units<br>
Draw a horizontal span (regtangle) from ymin to ymax. With the<br>
default values of xmin=0 and xmax=1, this always span the xrange,<br>
regardless of the xlim settings, even if you change them, eg with the<br>
xlim command. That is, the horizontal extent is in axes coords:<br>
0=left, 0.5=middle, 1.0=right but the y location is in data<br>
coordinates.<br>
kwargs are the kwargs to Patch, eg<br>
antialiased, aa<br>
linewidth, lw<br>
edgecolor, ec<br>
facecolor, fc<br>
the terms on the right are aliases<br>
Return value is the patches.Polygon instance.<br>
#draws a gray rectangle from y=0.25-0.75 that spans the horizontal<br>
#extent of the axes<br>
<a href="#Subplot-axhspan">axhspan</a>(0.25, 0.75, facecolor='0.5', alpha=0.5)<br>
Valid kwargs are Polygon properties<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-axis"><strong>axis</strong></a>(self, *v, **kwargs)</dt><dd><tt>Convenience method for manipulating the x and y view limits<br>
and the aspect ratio of the plot.<br>
<br>
kwargs are passed on to set_xlim and set_ylim -- see their docstrings for details</tt></dd></dl>
<dl><dt><a name="Subplot-axvline"><strong>axvline</strong></a>(self, x<font color="#909090">=0</font>, ymin<font color="#909090">=0</font>, ymax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXVLINE(x=0, ymin=0, ymax=1, **kwargs)<br>
Axis Vertical Line<br>
Draw a vertical line at x from ymin to ymax. With the default values<br>
of ymin=0 and ymax=1, this line will always span the vertical extent<br>
of the axes, regardless of the xlim settings, even if you change them,<br>
eg with the xlim command. That is, the vertical extent is in axes<br>
coords: 0=bottom, 0.5=middle, 1.0=top but the x location is in data<br>
coordinates.<br>
Return value is the Line2D instance. kwargs are the same as<br>
kwargs to plot, and can be used to control the line properties. Eg<br>
# draw a thick red vline at x=0 that spans the yrange<br>
l = <a href="#Subplot-axvline">axvline</a>(linewidth=4, color='r')<br>
# draw a default vline at x=1 that spans the yrange<br>
l = <a href="#Subplot-axvline">axvline</a>(x=1)<br>
# draw a default vline at x=.5 that spans the the middle half of<br>
# the yrange<br>
<a href="#Subplot-axvline">axvline</a>(x=.5, ymin=0.25, ymax=0.75)<br>
Valid kwargs are Line2D properties<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-axvspan"><strong>axvspan</strong></a>(self, xmin, xmax, ymin<font color="#909090">=0</font>, ymax<font color="#909090">=1</font>, **kwargs)</dt><dd><tt>AXVSPAN(xmin, xmax, ymin=0, ymax=1, **kwargs)<br>
axvspan : Axis Vertical Span. xcoords are in data units and y coords<br>
are in axes (relative 0-1) units<br>
Draw a vertical span (regtangle) from xmin to xmax. With the default<br>
values of ymin=0 and ymax=1, this always span the yrange, regardless<br>
of the ylim settings, even if you change them, eg with the ylim<br>
command. That is, the vertical extent is in axes coords: 0=bottom,<br>
0.5=middle, 1.0=top but the y location is in data coordinates.<br>
kwargs are the kwargs to Patch, eg<br>
antialiased, aa<br>
linewidth, lw<br>
edgecolor, ec<br>
facecolor, fc<br>
the terms on the right are aliases<br>
return value is the patches.Polygon instance.<br>
# draw a vertical green translucent rectangle from x=1.25 to 1.55 that<br>
# spans the yrange of the axes<br>
<a href="#Subplot-axvspan">axvspan</a>(1.25, 1.55, facecolor='g', alpha=0.5)<br>
Valid kwargs are Polygon properties<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-bar"><strong>bar</strong></a>(self, left, height, width<font color="#909090">=0.80000000000000004</font>, bottom<font color="#909090">=None</font>, color<font color="#909090">=None</font>, edgecolor<font color="#909090">=None</font>, linewidth<font color="#909090">=None</font>, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, ecolor<font color="#909090">=None</font>, capsize<font color="#909090">=3</font>, align<font color="#909090">='edge'</font>, orientation<font color="#909090">='vertical'</font>, log<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>BAR(left, height, width=0.8, bottom=0,<br>
color=None, edgecolor=None, linewidth=None,<br>
yerr=None, xerr=None, ecolor=None, capsize=3,<br>
align='edge', orientation='vertical', log=False)<br>
Make a bar plot with rectangles bounded by<br>
left, left+width, bottom, bottom+height<br>
(left, right, bottom and top edges)<br>
left, height, width, and bottom can be either scalars or sequences<br>
Return value is a list of Rectangle patch instances<br>
left - the x coordinates of the left sides of the bars<br>
height - the heights of the bars<br>
Optional arguments:<br>
width - the widths of the bars<br>
bottom - the y coordinates of the bottom edges of the bars<br>
color - the colors of the bars<br>
edgecolor - the colors of the bar edges<br>
linewidth - width of bar edges; None means use default<br>
linewidth; 0 means don't draw edges.<br>
xerr and yerr, if not None, will be used to generate errorbars<br>
on the bar chart<br>
ecolor specifies the color of any errorbar<br>
capsize (default 3) determines the length in points of the error<br>
bar caps<br>
align = 'edge' (default) | 'center'<br>
orientation = 'vertical' | 'horizontal'<br>
log = False | True - False (default) leaves the orientation<br>
axis as-is; True sets it to log scale<br>
For vertical bars, align='edge' aligns bars by their left edges in<br>
left, while 'center' interprets these values as the x coordinates of<br>
the bar centers. For horizontal bars, 'edge' aligns bars by their<br>
bottom edges in bottom, while 'center' interprets these values as the<br>
y coordinates of the bar centers.<br>
The optional arguments color, edgecolor, linewidth, xerr, and yerr can<br>
be either scalars or sequences of length equal to the number of bars.<br>
This enables you to use bar as the basis for stacked bar charts, or<br>
candlestick plots.<br>
Optional kwargs:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-barh"><strong>barh</strong></a>(self, bottom, width, height<font color="#909090">=0.80000000000000004</font>, left<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>BARH(bottom, width, height=0.8, left=0, **kwargs)<br>
Make a horizontal bar plot with rectangles bounded by<br>
left, left+width, bottom, bottom+height<br>
(left, right, bottom and top edges)<br>
bottom, width, height, and left can be either scalars or sequences<br>
Return value is a list of Rectangle patch instances<br>
bottom - the vertical positions of the bottom edges of the bars<br>
width - the lengths of the bars<br>
Optional arguments:<br>
height - the heights (thicknesses) of the bars<br>
left - the x coordinates of the left edges of the bars<br>
color - the colors of the bars<br>
edgecolor - the colors of the bar edges<br>
linewidth - width of bar edges; None means use default<br>
linewidth; 0 means don't draw edges.<br>
xerr and yerr, if not None, will be used to generate errorbars<br>
on the bar chart<br>
ecolor specifies the color of any errorbar<br>
capsize (default 3) determines the length in points of the error<br>
bar caps<br>
align = 'edge' (default) | 'center'<br>
log = False | True - False (default) leaves the horizontal<br>
axis as-is; True sets it to log scale<br>
Setting align='edge' aligns bars by their bottom edges in bottom,<br>
while 'center' interprets these values as the y coordinates of the bar<br>
centers.<br>
The optional arguments color, edgecolor, linewidth, xerr, and yerr can<br>
be either scalars or sequences of length equal to the number of bars.<br>
This enables you to use barh as the basis for stacked bar charts, or<br>
candlestick plots.<br>
Optional kwargs:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-boxplot"><strong>boxplot</strong></a>(self, x, notch<font color="#909090">=0</font>, sym<font color="#909090">='b+'</font>, vert<font color="#909090">=1</font>, whis<font color="#909090">=1.5</font>, positions<font color="#909090">=None</font>, widths<font color="#909090">=None</font>)</dt><dd><tt><a href="#Subplot-boxplot">boxplot</a>(x, notch=0, sym='+', vert=1, whis=1.5,<br>
positions=None, widths=None)<br>
<br>
Make a box and whisker plot for each column of x or<br>
each vector in sequence x.<br>
The box extends from the lower to upper quartile values<br>
of the data, with a line at the median. The whiskers<br>
extend from the box to show the range of the data. Flier<br>
points are those past the end of the whiskers.<br>
<br>
notch = 0 (default) produces a rectangular box plot.<br>
notch = 1 will produce a notched box plot<br>
<br>
sym (default 'b+') is the default symbol for flier points.<br>
Enter an empty string ('') if you don't want to show fliers.<br>
<br>
vert = 1 (default) makes the boxes vertical.<br>
vert = 0 makes horizontal boxes. This seems goofy, but<br>
that's how Matlab did it.<br>
<br>
whis (default 1.5) defines the length of the whiskers as<br>
a function of the inner quartile range. They extend to the<br>
most extreme data point within ( whis*(75%-25%) ) data range.<br>
<br>
positions (default 1,2,...,n) sets the horizontal positions of<br>
the boxes. The ticks and limits are automatically set to match<br>
the positions.<br>
<br>
widths is either a scalar or a vector and sets the width of<br>
each box. The default is 0.5, or 0.15*(distance between extreme<br>
positions) if that is smaller.<br>
<br>
x is an array or a sequence of vectors.<br>
<br>
Returns a list of the lines added.</tt></dd></dl>
<dl><dt><a name="Subplot-broken_barh"><strong>broken_barh</strong></a>(self, xranges, yrange, **kwargs)</dt><dd><tt>A collection of horizontal bars spanning yrange with a sequence of<br>
xranges<br>
xranges : sequence of (xmin, xwidth)<br>
yrange : (ymin, ywidth)<br>
kwargs are collections.BrokenBarHCollection properties<br>
alpha: float<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
edgecolor: matplotlib color arg or sequence of rgba tuples<br>
facecolor: matplotlib color arg or sequence of rgba tuples<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number<br>
these can either be a single argument, ie facecolors='black'<br>
or a sequence of arguments for the various bars, ie<br>
facecolors='black', 'red', 'green'</tt></dd></dl>
<dl><dt><a name="Subplot-cla"><strong>cla</strong></a>(self)</dt><dd><tt>Clear the current axes</tt></dd></dl>
<dl><dt><a name="Subplot-clabel"><strong>clabel</strong></a>(self, CS, *args, **kwargs)</dt><dd><tt><a href="#Subplot-clabel">clabel</a>(CS, **kwargs) - add labels to line contours in CS,<br>
where CS is a ContourSet object returned by contour.<br>
<br>
<a href="#Subplot-clabel">clabel</a>(CS, V, **kwargs) - only label contours listed in V<br>
<br>
keyword arguments:<br>
<br>
* fontsize = None: as described in <a href="http://matplotlib.sf.net/fonts.html">http://matplotlib.sf.net/fonts.html</a><br>
<br>
* colors = None:<br>
<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different labels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all labels<br>
will be plotted in this color<br>
<br>
- if colors == None, the color of each label matches the color<br>
of the corresponding contour<br>
<br>
* inline = True: controls whether the underlying contour is removed<br>
(inline = True) or not (False)<br>
<br>
* fmt = '%1.3f': a format string for the label</tt></dd></dl>
<dl><dt><a name="Subplot-clear"><strong>clear</strong></a>(self)</dt><dd><tt>clear the axes</tt></dd></dl>
<dl><dt><a name="Subplot-cohere"><strong>cohere</strong></a>(self, x, y, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, window<font color="#909090">=<function window_hanning at 0xb5bc7764></font>, noverlap<font color="#909090">=0</font>, **kwargs)</dt><dd><tt>COHERE(x, y, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0, **kwargs)<br>
cohere the coherence between x and y. Coherence is the normalized<br>
cross spectral density<br>
Cxy = |Pxy|^2/(Pxx*Pyy)<br>
The return value is (Cxy, f), where f are the frequencies of the<br>
coherence vector.<br>
See the PSD help for a description of the optional parameters.<br>
kwargs are applied to the lines<br>
Returns the tuple Cxy, freqs<br>
Refs: Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)<br>
kwargs control the Line2D properties of the coherence plot:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-connect"><strong>connect</strong></a>(self, s, func)</dt><dd><tt>Register observers to be notified when certain events occur. Register<br>
with callback functions with the following signatures. The function<br>
has the following signature<br>
<br>
func(ax) # where ax is the instance making the callback.<br>
<br>
The following events can be connected to:<br>
<br>
'xlim_changed','ylim_changed'<br>
<br>
The connection id is is returned - you can use this with<br>
disconnect to disconnect from the axes event</tt></dd></dl>
<dl><dt><a name="Subplot-contour"><strong>contour</strong></a>(self, *args, **kwargs)</dt><dd><tt>contour and contourf draw contour lines and filled contours,<br>
respectively. Except as noted, function signatures and return<br>
values are the same for both versions.<br>
<br>
contourf differs from the Matlab (TM) version in that it does not<br>
draw the polygon edges, because the contouring engine yields<br>
simply connected regions with branch cuts. To draw the edges,<br>
add line contours with calls to contour.<br>
<br>
<br>
Function signatures<br>
<br>
<a href="#Subplot-contour">contour</a>(Z) - make a contour plot of an array Z. The level<br>
values are chosen automatically.<br>
<br>
<a href="#Subplot-contour">contour</a>(X,Y,Z) - X,Y specify the (x,y) coordinates of the surface<br>
<br>
<a href="#Subplot-contour">contour</a>(Z,N) and <a href="#Subplot-contour">contour</a>(X,Y,Z,N) - contour N automatically-chosen<br>
levels.<br>
<br>
<a href="#Subplot-contour">contour</a>(Z,V) and <a href="#Subplot-contour">contour</a>(X,Y,Z,V) - draw len(V) contour lines,<br>
at the values specified in sequence V<br>
<br>
<a href="#Subplot-contourf">contourf</a>(..., V) - fill the (len(V)-1) regions between the<br>
values in V<br>
<br>
<a href="#Subplot-contour">contour</a>(Z, **kwargs) - Use keyword args to control colors, linewidth,<br>
origin, cmap ... see below<br>
<br>
X, Y, and Z must be arrays with the same dimensions.<br>
Z may be a masked array, but filled contouring may not handle<br>
internal masked regions correctly.<br>
<br>
C = <a href="#Subplot-contour">contour</a>(...) returns a ContourSet object.<br>
<br>
<br>
Optional keyword args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* colors = None; or one of the following:<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different levels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all levels<br>
will be plotted in this color<br>
<br>
- if colors == None, the colormap specified by cmap will be used<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
* cmap = None: a cm Colormap instance from matplotlib.cm.<br>
- if cmap == None and colors == None, a default Colormap is used.<br>
<br>
* norm = None: a matplotlib.colors.Normalize instance for<br>
scaling data values to colors.<br>
- if norm == None, and colors == None, the default<br>
linear scaling is used.<br>
<br>
* origin = None: 'upper'|'lower'|'image'|None.<br>
If 'image', the rc value for image.origin will be used.<br>
If None (default), the first value of Z will correspond<br>
to the lower left corner, location (0,0).<br>
This keyword is active only if contourf is called with<br>
one or two arguments, that is, without explicitly<br>
specifying X and Y.<br>
<br>
* extent = None: (x0,x1,y0,y1); also active only if X and Y<br>
are not specified. If origin is not None, then extent is<br>
interpreted as in imshow: it gives the outer pixel boundaries.<br>
In this case, the position of Z[0,0] is the center of the<br>
pixel, not a corner.<br>
If origin is None, then (x0,y0) is the position of Z[0,0],<br>
and (x1,y1) is the position of Z[-1,-1].<br>
<br>
* locator = None: an instance of a ticker.Locator subclass;<br>
default is MaxNLocator. It is used to determine the<br>
contour levels if they are not given explicitly via the<br>
V argument.<br>
<br>
***** New: *****<br>
* extend = 'neither', 'both', 'min', 'max'<br>
Unless this is 'neither' (default), contour levels are<br>
automatically added to one or both ends of the range so that<br>
all data are included. These added ranges are then<br>
mapped to the special colormap values which default to<br>
the ends of the colormap range, but can be set via<br>
Colormap.set_under() and Colormap.set_over() methods.<br>
To replace clip_ends=True and V = [-100, 2, 1, 0, 1, 2, 100],<br>
use extend='both' and V = [2, 1, 0, 1, 2].<br>
****************<br>
<br>
contour only:<br>
* linewidths = None: or one of these:<br>
- a number - all levels will be plotted with this linewidth,<br>
e.g. linewidths = 0.6<br>
<br>
- a tuple of numbers, e.g. linewidths = (0.4, 0.8, 1.2) different<br>
levels will be plotted with different linewidths in the order<br>
specified<br>
<br>
- if linewidths == None, the default width in lines.linewidth in<br>
matplotlibrc is used<br>
<br>
contourf only:<br>
***** Obsolete: ****<br>
* clip_ends = True<br>
If False, the limits for color scaling are set to the<br>
minimum and maximum contour levels.<br>
True (default) clips the scaling limits. Example:<br>
if the contour boundaries are V = [-100, 2, 1, 0, 1, 2, 100],<br>
then the scaling limits will be [-100, 100] if clip_ends<br>
is False, and [-3, 3] if clip_ends is True.<br>
* linewidths = None or a number; default of 0.05 works for<br>
Postscript; a value of about 0.5 seems better for Agg.<br>
* antialiased = True (default) or False; if False, there is<br>
no need to increase the linewidths for Agg, but True gives<br>
nicer color boundaries. If antialiased is True and linewidths<br>
is too small, then there may be light-colored lines at the<br>
color boundaries caused by the antialiasing.<br>
* nchunk = 0 (default) for no subdivision of the domain;<br>
specify a positive integer to divide the domain into<br>
subdomains of roughly nchunk by nchunk points. This may<br>
never actually be advantageous, so this option may be<br>
removed. Chunking introduces artifacts at the chunk<br>
boundaries unless antialiased = False, or linewidths is<br>
set to a large enough value for the particular renderer and<br>
resolution.</tt></dd></dl>
<dl><dt><a name="Subplot-contourf"><strong>contourf</strong></a>(self, *args, **kwargs)</dt><dd><tt>contour and contourf draw contour lines and filled contours,<br>
respectively. Except as noted, function signatures and return<br>
values are the same for both versions.<br>
<br>
contourf differs from the Matlab (TM) version in that it does not<br>
draw the polygon edges, because the contouring engine yields<br>
simply connected regions with branch cuts. To draw the edges,<br>
add line contours with calls to contour.<br>
<br>
<br>
Function signatures<br>
<br>
<a href="#Subplot-contour">contour</a>(Z) - make a contour plot of an array Z. The level<br>
values are chosen automatically.<br>
<br>
<a href="#Subplot-contour">contour</a>(X,Y,Z) - X,Y specify the (x,y) coordinates of the surface<br>
<br>
<a href="#Subplot-contour">contour</a>(Z,N) and <a href="#Subplot-contour">contour</a>(X,Y,Z,N) - contour N automatically-chosen<br>
levels.<br>
<br>
<a href="#Subplot-contour">contour</a>(Z,V) and <a href="#Subplot-contour">contour</a>(X,Y,Z,V) - draw len(V) contour lines,<br>
at the values specified in sequence V<br>
<br>
<a href="#Subplot-contourf">contourf</a>(..., V) - fill the (len(V)-1) regions between the<br>
values in V<br>
<br>
<a href="#Subplot-contour">contour</a>(Z, **kwargs) - Use keyword args to control colors, linewidth,<br>
origin, cmap ... see below<br>
<br>
X, Y, and Z must be arrays with the same dimensions.<br>
Z may be a masked array, but filled contouring may not handle<br>
internal masked regions correctly.<br>
<br>
C = <a href="#Subplot-contour">contour</a>(...) returns a ContourSet object.<br>
<br>
<br>
Optional keyword args are shown with their defaults below (you must<br>
use kwargs for these):<br>
<br>
* colors = None; or one of the following:<br>
- a tuple of matplotlib color args (string, float, rgb, etc),<br>
different levels will be plotted in different colors in the order<br>
specified<br>
<br>
- one string color, e.g. colors = 'r' or colors = 'red', all levels<br>
will be plotted in this color<br>
<br>
- if colors == None, the colormap specified by cmap will be used<br>
<br>
* alpha=1.0 : the alpha blending value<br>
<br>
* cmap = None: a cm Colormap instance from matplotlib.cm.<br>
- if cmap == None and colors == None, a default Colormap is used.<br>
<br>
* norm = None: a matplotlib.colors.Normalize instance for<br>
scaling data values to colors.<br>
- if norm == None, and colors == None, the default<br>
linear scaling is used.<br>
<br>
* origin = None: 'upper'|'lower'|'image'|None.<br>
If 'image', the rc value for image.origin will be used.<br>
If None (default), the first value of Z will correspond<br>
to the lower left corner, location (0,0).<br>
This keyword is active only if contourf is called with<br>
one or two arguments, that is, without explicitly<br>
specifying X and Y.<br>
<br>
* extent = None: (x0,x1,y0,y1); also active only if X and Y<br>
are not specified. If origin is not None, then extent is<br>
interpreted as in imshow: it gives the outer pixel boundaries.<br>
In this case, the position of Z[0,0] is the center of the<br>
pixel, not a corner.<br>
If origin is None, then (x0,y0) is the position of Z[0,0],<br>
and (x1,y1) is the position of Z[-1,-1].<br>
<br>
* locator = None: an instance of a ticker.Locator subclass;<br>
default is MaxNLocator. It is used to determine the<br>
contour levels if they are not given explicitly via the<br>
V argument.<br>
<br>
***** New: *****<br>
* extend = 'neither', 'both', 'min', 'max'<br>
Unless this is 'neither' (default), contour levels are<br>
automatically added to one or both ends of the range so that<br>
all data are included. These added ranges are then<br>
mapped to the special colormap values which default to<br>
the ends of the colormap range, but can be set via<br>
Colormap.set_under() and Colormap.set_over() methods.<br>
To replace clip_ends=True and V = [-100, 2, 1, 0, 1, 2, 100],<br>
use extend='both' and V = [2, 1, 0, 1, 2].<br>
****************<br>
<br>
contour only:<br>
* linewidths = None: or one of these:<br>
- a number - all levels will be plotted with this linewidth,<br>
e.g. linewidths = 0.6<br>
<br>
- a tuple of numbers, e.g. linewidths = (0.4, 0.8, 1.2) different<br>
levels will be plotted with different linewidths in the order<br>
specified<br>
<br>
- if linewidths == None, the default width in lines.linewidth in<br>
matplotlibrc is used<br>
<br>
contourf only:<br>
***** Obsolete: ****<br>
* clip_ends = True<br>
If False, the limits for color scaling are set to the<br>
minimum and maximum contour levels.<br>
True (default) clips the scaling limits. Example:<br>
if the contour boundaries are V = [-100, 2, 1, 0, 1, 2, 100],<br>
then the scaling limits will be [-100, 100] if clip_ends<br>
is False, and [-3, 3] if clip_ends is True.<br>
* linewidths = None or a number; default of 0.05 works for<br>
Postscript; a value of about 0.5 seems better for Agg.<br>
* antialiased = True (default) or False; if False, there is<br>
no need to increase the linewidths for Agg, but True gives<br>
nicer color boundaries. If antialiased is True and linewidths<br>
is too small, then there may be light-colored lines at the<br>
color boundaries caused by the antialiasing.<br>
* nchunk = 0 (default) for no subdivision of the domain;<br>
specify a positive integer to divide the domain into<br>
subdomains of roughly nchunk by nchunk points. This may<br>
never actually be advantageous, so this option may be<br>
removed. Chunking introduces artifacts at the chunk<br>
boundaries unless antialiased = False, or linewidths is<br>
set to a large enough value for the particular renderer and<br>
resolution.</tt></dd></dl>
<dl><dt><a name="Subplot-csd"><strong>csd</strong></a>(self, x, y, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, window<font color="#909090">=<function window_hanning at 0xb5bc7764></font>, noverlap<font color="#909090">=0</font>, **kwargs)</dt><dd><tt>CSD(x, y, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0, **kwargs)<br>
The cross spectral density Pxy by Welches average periodogram method.<br>
The vectors x and y are divided into NFFT length segments. Each<br>
segment is detrended by function detrend and windowed by function<br>
window. The product of the direct FFTs of x and y are averaged over<br>
each segment to compute Pxy, with a scaling to correct for power loss<br>
due to windowing.<br>
See the PSD help for a description of the optional parameters.<br>
Returns the tuple Pxy, freqs. Pxy is the cross spectrum (complex<br>
valued), and 10*log10(|Pxy|) is plotted<br>
Refs:<br>
Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)<br>
kwargs control the Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-disconnect"><strong>disconnect</strong></a>(self, cid)</dt><dd><tt>disconnect from the <a href="#Axes">Axes</a> event.</tt></dd></dl>
<dl><dt><a name="Subplot-draw"><strong>draw</strong></a>(self, renderer<font color="#909090">=None</font>, inframe<font color="#909090">=False</font>)</dt><dd><tt>Draw everything (plot lines, axes, labels)</tt></dd></dl>
<dl><dt><a name="Subplot-draw_artist"><strong>draw_artist</strong></a>(self, a)</dt><dd><tt>This method can only be used after an initial draw which<br>
caches the renderer. It is used to efficiently update <a href="#Axes">Axes</a><br>
data (axis ticks, labels, etc are not updated)</tt></dd></dl>
<dl><dt><a name="Subplot-errorbar"><strong>errorbar</strong></a>(self, x, y, yerr<font color="#909090">=None</font>, xerr<font color="#909090">=None</font>, fmt<font color="#909090">='b-'</font>, ecolor<font color="#909090">=None</font>, capsize<font color="#909090">=3</font>, barsabove<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>ERRORBAR(x, y, yerr=None, xerr=None,<br>
fmt='b-', ecolor=None, capsize=3, barsabove=False)<br>
Plot x versus y with error deltas in yerr and xerr.<br>
Vertical errorbars are plotted if yerr is not None<br>
Horizontal errorbars are plotted if xerr is not None<br>
xerr and yerr may be any of:<br>
a rank-0, Nx1 Numpy array - symmetric errorbars +/- value<br>
an N-element list or tuple - symmetric errorbars +/- value<br>
a rank-1, Nx2 Numpy array - asymmetric errorbars -column1/+column2<br>
Alternatively, x, y, xerr, and yerr can all be scalars, which<br>
plots a single error bar at x, y.<br>
fmt is the plot format symbol for y. if fmt is None, just<br>
plot the errorbars with no line symbols. This can be useful<br>
for creating a bar plot with errorbars<br>
ecolor is a matplotlib color arg which gives the color the<br>
errorbar lines; if None, use the marker color.<br>
capsize is the size of the error bar caps in points<br>
barsabove, if True, will plot the errorbars above the plot symbols<br>
- default is below<br>
kwargs are passed on to the plot command for the markers.<br>
So you can add additional key=value pairs to control the<br>
errorbar markers. For example, this code makes big red<br>
squares with thick green edges<br>
>>> x,y,yerr = rand(3,10)<br>
>>> <a href="#Subplot-errorbar">errorbar</a>(x, y, yerr, marker='s',<br>
mfc='red', mec='green', ms=20, mew=4)<br>
mfc, mec, ms and mew are aliases for the longer property<br>
names, markerfacecolor, markeredgecolor, markersize and<br>
markeredgewith.<br>
valid kwargs for the marker properties are<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number<br>
Return value is a length 3 tuple. The first element is the<br>
Line2D instance for the y symbol lines. The second element is<br>
a list of error bar cap lines, the third element is a list of<br>
line collections for the horizontal and vertical error ranges</tt></dd></dl>
<dl><dt><a name="Subplot-fill"><strong>fill</strong></a>(self, *args, **kwargs)</dt><dd><tt>FILL(*args, **kwargs)<br>
plot filled polygons. *args is a variable length argument, allowing<br>
for multiple x,y pairs with an optional color format string; see plot<br>
for details on the argument parsing. For example, all of the<br>
following are legal, assuming ax is an <a href="#Axes">Axes</a> instance:<br>
ax.<a href="#Subplot-fill">fill</a>(x,y) # plot polygon with vertices at x,y<br>
ax.<a href="#Subplot-fill">fill</a>(x,y, 'b' ) # plot polygon with vertices at x,y in blue<br>
An arbitrary number of x, y, color groups can be specified, as in<br>
ax.<a href="#Subplot-fill">fill</a>(x1, y1, 'g', x2, y2, 'r')<br>
Return value is a list of patches that were added<br>
The same color strings that plot supports are supported by the fill<br>
format string.<br>
kwargs control the Polygon properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-format_coord"><strong>format_coord</strong></a>(self, x, y)</dt><dd><tt>return a format string formatting the x, y coord</tt></dd></dl>
<dl><dt><a name="Subplot-format_xdata"><strong>format_xdata</strong></a>(self, x)</dt><dd><tt>Return x string formatted. This function will use the attribute<br>
self.<strong>fmt_xdata</strong> if it is callable, else will fall back on the xaxis<br>
major formatter</tt></dd></dl>
<dl><dt><a name="Subplot-format_ydata"><strong>format_ydata</strong></a>(self, y)</dt><dd><tt>Return y string formatted. This function will use the attribute<br>
self.<strong>fmt_ydata</strong> if it is callable, else will fall back on the yaxis<br>
major formatter</tt></dd></dl>
<dl><dt><a name="Subplot-get_adjustable"><strong>get_adjustable</strong></a>(self)</dt></dl>
<dl><dt><a name="Subplot-get_anchor"><strong>get_anchor</strong></a>(self)</dt></dl>
<dl><dt><a name="Subplot-get_aspect"><strong>get_aspect</strong></a>(self)</dt></dl>
<dl><dt><a name="Subplot-get_autoscale_on"><strong>get_autoscale_on</strong></a>(self)</dt><dd><tt>Get whether autoscaling is applied on plot commands</tt></dd></dl>
<dl><dt><a name="Subplot-get_axis_bgcolor"><strong>get_axis_bgcolor</strong></a>(self)</dt><dd><tt>Return the axis background color</tt></dd></dl>
<dl><dt><a name="Subplot-get_axisbelow"><strong>get_axisbelow</strong></a>(self)</dt><dd><tt>Get whether axist below is true or not</tt></dd></dl>
<dl><dt><a name="Subplot-get_child_artists"><strong>get_child_artists</strong></a>(self)</dt><dd><tt>Return a list of artists the axes contains. Deprecated</tt></dd></dl>
<dl><dt><a name="Subplot-get_children"><strong>get_children</strong></a>(self)</dt><dd><tt>return a list of child artists</tt></dd></dl>
<dl><dt><a name="Subplot-get_cursor_props"><strong>get_cursor_props</strong></a>(self)</dt><dd><tt>return the cursor props as a linewidth, color tuple where<br>
linewidth is a float and color is an RGBA tuple</tt></dd></dl>
<dl><dt><a name="Subplot-get_frame"><strong>get_frame</strong></a>(self)</dt><dd><tt>Return the axes Rectangle frame</tt></dd></dl>
<dl><dt><a name="Subplot-get_frame_on"><strong>get_frame_on</strong></a>(self)</dt><dd><tt>Get whether the axes rectangle patch is drawn</tt></dd></dl>
<dl><dt><a name="Subplot-get_images"><strong>get_images</strong></a>(self)</dt><dd><tt>return a list of <a href="#Axes">Axes</a> images contained by the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="Subplot-get_legend"><strong>get_legend</strong></a>(self)</dt><dd><tt>Return the Legend instance, or None if no legend is defined</tt></dd></dl>
<dl><dt><a name="Subplot-get_lines"><strong>get_lines</strong></a>(self)</dt><dd><tt>Return a list of lines contained by the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="Subplot-get_navigate"><strong>get_navigate</strong></a>(self)</dt><dd><tt>Get whether the axes responds to navigation commands</tt></dd></dl>
<dl><dt><a name="Subplot-get_navigate_mode"><strong>get_navigate_mode</strong></a>(self)</dt><dd><tt>Get the navigation toolbar button status: 'PAN', 'ZOOM', or None</tt></dd></dl>
<dl><dt><a name="Subplot-get_position"><strong>get_position</strong></a>(self, original<font color="#909090">=False</font>)</dt><dd><tt>Return the axes rectangle left, bottom, width, height</tt></dd></dl>
<dl><dt><a name="Subplot-get_renderer_cache"><strong>get_renderer_cache</strong></a>(self)</dt></dl>
<dl><dt><a name="Subplot-get_window_extent"><strong>get_window_extent</strong></a>(self, *args, **kwargs)</dt><dd><tt>get the axes bounding box in display space; args and kwargs are empty</tt></dd></dl>
<dl><dt><a name="Subplot-get_xaxis"><strong>get_xaxis</strong></a>(self)</dt><dd><tt>Return the XAxis instance</tt></dd></dl>
<dl><dt><a name="Subplot-get_xgridlines"><strong>get_xgridlines</strong></a>(self)</dt><dd><tt>Get the x grid lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="Subplot-get_xlim"><strong>get_xlim</strong></a>(self)</dt><dd><tt>Get the x axis range [xmin, xmax]</tt></dd></dl>
<dl><dt><a name="Subplot-get_xscale"><strong>get_xscale</strong></a>(self)</dt><dd><tt>return the xaxis scale string: log or linear</tt></dd></dl>
<dl><dt><a name="Subplot-get_xticklabels"><strong>get_xticklabels</strong></a>(self)</dt><dd><tt>Get the xtick labels as a list of Text instances</tt></dd></dl>
<dl><dt><a name="Subplot-get_xticklines"><strong>get_xticklines</strong></a>(self)</dt><dd><tt>Get the xtick lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="Subplot-get_xticks"><strong>get_xticks</strong></a>(self)</dt><dd><tt>Return the x ticks as a list of locations</tt></dd></dl>
<dl><dt><a name="Subplot-get_yaxis"><strong>get_yaxis</strong></a>(self)</dt><dd><tt>Return the YAxis instance</tt></dd></dl>
<dl><dt><a name="Subplot-get_ygridlines"><strong>get_ygridlines</strong></a>(self)</dt><dd><tt>Get the y grid lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="Subplot-get_ylim"><strong>get_ylim</strong></a>(self)</dt><dd><tt>Get the y axis range [ymin, ymax]</tt></dd></dl>
<dl><dt><a name="Subplot-get_yscale"><strong>get_yscale</strong></a>(self)</dt><dd><tt>return the yaxis scale string: log or linear</tt></dd></dl>
<dl><dt><a name="Subplot-get_yticklabels"><strong>get_yticklabels</strong></a>(self)</dt><dd><tt>Get the ytick labels as a list of Text instances</tt></dd></dl>
<dl><dt><a name="Subplot-get_yticklines"><strong>get_yticklines</strong></a>(self)</dt><dd><tt>Get the ytick lines as a list of Line2D instances</tt></dd></dl>
<dl><dt><a name="Subplot-get_yticks"><strong>get_yticks</strong></a>(self)</dt><dd><tt>Return the y ticks as a list of locations</tt></dd></dl>
<dl><dt><a name="Subplot-grid"><strong>grid</strong></a>(self, b<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>GRID(self, b=None, **kwargs)<br>
Set the axes grids on or off; b is a boolean<br>
if b is None and len(kwargs)==0, toggle the grid state. if<br>
kwargs are supplied, it is assumed that you want a grid and b<br>
is thus set to True<br>
kawrgs are used to set the grid line properties, eg<br>
ax.<a href="#Subplot-grid">grid</a>(color='r', linestyle='-', linewidth=2)<br>
Valid Line2D kwargs are<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-has_data"><strong>has_data</strong></a>(self)</dt><dd><tt>Return true if any artists have been added to axes.<br>
<br>
This should not be used to determine whether the dataLim<br>
need to be updated, and may not actually be useful for<br>
anything.</tt></dd></dl>
<dl><dt><a name="Subplot-hist"><strong>hist</strong></a>(self, x, bins<font color="#909090">=10</font>, normed<font color="#909090">=0</font>, bottom<font color="#909090">=None</font>, align<font color="#909090">='edge'</font>, orientation<font color="#909090">='vertical'</font>, width<font color="#909090">=None</font>, log<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>HIST(x, bins=10, normed=0, bottom=None,<br>
align='edge', orientation='vertical', width=None,<br>
log=False, **kwargs)<br>
Compute the histogram of x. bins is either an integer number of<br>
bins or a sequence giving the bins. x are the data to be binned.<br>
The return values is (n, bins, patches)<br>
If normed is true, the first element of the return tuple will<br>
be the counts normalized to form a probability density, ie,<br>
n/(len(x)*dbin). In a probability density, the integral of<br>
the histogram should be one (we assume equally spaced bins);<br>
you can verify that with<br>
# trapezoidal integration of the probability density function<br>
from matplotlib.mlab import trapz<br>
pdf, bins, patches = ax.<a href="#Subplot-hist">hist</a>(...)<br>
print trapz(bins, pdf)<br>
align = 'edge' | 'center'. Interprets bins either as edge<br>
or center values<br>
orientation = 'horizontal' | 'vertical'. If horizontal, barh<br>
will be used and the "bottom" kwarg will be the left edges.<br>
width: the width of the bars. If None, automatically compute<br>
the width.<br>
log: if True, the histogram axis will be set to a log scale<br>
kwargs are used to update the properties of the<br>
hist Rectangles:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
edgecolor or ec: any matplotlib color<br>
facecolor or fc: any matplotlib color<br>
figure: a matplotlib.figure.Figure instance<br>
fill: [True | False]<br>
hatch: unknown<br>
label: any string<br>
linewidth or lw: float<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-hlines"><strong>hlines</strong></a>(self, y, xmin, xmax, colors<font color="#909090">='k'</font>, linestyle<font color="#909090">='solid'</font>, label<font color="#909090">=''</font>, **kwargs)</dt><dd><tt>HLINES(y, xmin, xmax, colors='k', linestyle='solid', **kwargs)<br>
plot horizontal lines at each y from xmin to xmax. xmin or xmax can<br>
be scalars or len(x) numpy arrays. If they are scalars, then the<br>
respective values are constant, else the widths of the lines are<br>
determined by xmin and xmax<br>
colors is a line collections color args, either a single color or a len(x) list of colors<br>
linestyle is one of solid|dashed|dashdot|dotted<br>
Returns the LineCollection that was added</tt></dd></dl>
<dl><dt><a name="Subplot-hold"><strong>hold</strong></a>(self, b<font color="#909090">=None</font>)</dt><dd><tt>HOLD(b=None)<br>
<br>
Set the hold state. If hold is None (default), toggle the<br>
hold state. Else set the hold state to boolean value b.<br>
<br>
Eg<br>
<a href="#Subplot-hold">hold</a>() # toggle hold<br>
<a href="#Subplot-hold">hold</a>(True) # hold is on<br>
<a href="#Subplot-hold">hold</a>(False) # hold is off<br>
<br>
<br>
When hold is True, subsequent plot commands will be added to<br>
the current axes. When hold is False, the current axes and<br>
figure will be cleared on the next plot command</tt></dd></dl>
<dl><dt><a name="Subplot-imshow"><strong>imshow</strong></a>(self, X, cmap<font color="#909090">=None</font>, norm<font color="#909090">=None</font>, aspect<font color="#909090">=None</font>, interpolation<font color="#909090">=None</font>, alpha<font color="#909090">=1.0</font>, vmin<font color="#909090">=None</font>, vmax<font color="#909090">=None</font>, origin<font color="#909090">=None</font>, extent<font color="#909090">=None</font>, shape<font color="#909090">=None</font>, filternorm<font color="#909090">=1</font>, filterrad<font color="#909090">=4.0</font>, imlim<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>IMSHOW(X, cmap=None, norm=None, aspect=None, interpolation=None,<br>
alpha=1.0, vmin=None, vmax=None, origin=None, extent=None)<br>
<br>
IMSHOW(X) - plot image X to current axes, resampling to scale to axes<br>
size (X may be numarray/Numeric array or PIL image)<br>
<br>
IMSHOW(X, **kwargs) - Use keyword args to control image scaling,<br>
colormapping etc. See below for details<br>
<br>
<br>
Display the image in X to current axes. X may be a float array, a<br>
UInt8 array or a PIL image. If X is an array, X can have the following<br>
shapes:<br>
<br>
MxN : luminance (grayscale, float array only)<br>
<br>
MxNx3 : RGB (float or UInt8 array)<br>
<br>
MxNx4 : RGBA (float or UInt8 array)<br>
<br>
The value for each component of MxNx3 and MxNx4 float arrays should be<br>
in the range 0.0 to 1.0; MxN float arrays may be normalised.<br>
<br>
A matplotlib.image.AxesImage instance is returned<br>
<br>
The following kwargs are allowed:<br>
<br>
* cmap is a cm colormap instance, eg cm.jet. If None, default to rc<br>
image.cmap value (Ignored when X has RGB(A) information)<br>
<br>
* aspect is one of: auto, equal, or a number. If None, default to rc<br>
image.aspect value<br>
<br>
* interpolation is one of:<br>
<br>
'nearest', 'bilinear', 'bicubic', 'spline16', 'spline36',<br>
'hanning', 'hamming', 'hermite', 'kaiser', 'quadric',<br>
'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc',<br>
'lanczos', 'blackman'<br>
<br>
if interpolation is None, default to rc<br>
image.interpolation. See also th the filternorm and<br>
filterrad parameters<br>
<br>
* norm is a matplotlib.colors.Normalize instance; default is<br>
normalization(). This scales luminance -> 0-1 (only used for an<br>
MxN float array).<br>
<br>
* vmin and vmax are used to scale a luminance image to 0-1. If<br>
either is None, the min and max of the luminance values will be<br>
used. Note if you pass a norm instance, the settings for vmin and<br>
vmax will be ignored.<br>
<br>
* alpha = 1.0 : the alpha blending value<br>
<br>
* origin is 'upper' or 'lower', to place the [0,0]<br>
index of the array in the upper left or lower left corner of<br>
the axes. If None, default to rc image.origin<br>
<br>
* extent is (left, right, bottom, top) data values of the<br>
axes. The default assigns zero-based row, column indices<br>
to the x, y centers of the pixels.<br>
<br>
* shape is for raw buffer images<br>
<br>
* filternorm is a parameter for the antigrain image resize<br>
filter. From the antigrain documentation, if normalize=1,<br>
the filter normalizes integer values and corrects the<br>
rounding errors. It doesn't do anything with the source<br>
floating point values, it corrects only integers according<br>
to the rule of 1.0 which means that any sum of pixel<br>
weights must be equal to 1.0. So, the filter function<br>
must produce a graph of the proper shape.<br>
<br>
* filterrad: the filter radius for filters that have a radius<br>
parameter, ie when interpolation is one of: 'sinc',<br>
'lanczos' or 'blackman'<br>
<br>
Additional kwargs are matplotlib.artist properties</tt></dd></dl>
<dl><dt><a name="Subplot-in_axes"><strong>in_axes</strong></a>(self, xwin, ywin)</dt><dd><tt>return True is the point xwin, ywin (display coords) are in the <a href="#Axes">Axes</a></tt></dd></dl>
<dl><dt><a name="Subplot-ishold"><strong>ishold</strong></a>(self)</dt><dd><tt>return the HOLD status of the axes</tt></dd></dl>
<dl><dt><a name="Subplot-legend"><strong>legend</strong></a>(self, *args, **kwargs)</dt><dd><tt>LEGEND(*args, **kwargs)<br>
<br>
Place a legend on the current axes at location loc. Labels are a<br>
sequence of strings and loc can be a string or an integer specifying<br>
the legend location<br>
<br>
USAGE:<br>
<br>
Make a legend with existing lines<br>
<br>
>>> <a href="#Subplot-legend">legend</a>()<br>
<br>
legend by itself will try and build a legend using the label<br>
property of the lines/patches/collections. You can set the label of<br>
a line by doing <a href="#Subplot-plot">plot</a>(x, y, label='my data') or line.<a href="#Subplot-set_label">set_label</a>('my<br>
data'). If label is set to '_nolegend_', the item will not be shown<br>
in legend.<br>
<br>
# automatically generate the legend from labels<br>
<a href="#Subplot-legend">legend</a>( ('label1', 'label2', 'label3') )<br>
<br>
# Make a legend for a list of lines and labels<br>
<a href="#Subplot-legend">legend</a>( (line1, line2, line3), ('label1', 'label2', 'label3') )<br>
<br>
# Make a legend at a given location, using a location argument<br>
# <a href="#Subplot-legend">legend</a>( LABELS, LOC ) or<br>
# <a href="#Subplot-legend">legend</a>( LINES, LABELS, LOC )<br>
<a href="#Subplot-legend">legend</a>( ('label1', 'label2', 'label3'), loc='upper left')<br>
<a href="#Subplot-legend">legend</a>( (line1, line2, line3), ('label1', 'label2', 'label3'), loc=2)<br>
<br>
The location codes are<br>
<br>
'best' : 0,<br>
'upper right' : 1, (default)<br>
'upper left' : 2,<br>
'lower left' : 3,<br>
'lower right' : 4,<br>
'right' : 5,<br>
'center left' : 6,<br>
'center right' : 7,<br>
'lower center' : 8,<br>
'upper center' : 9,<br>
'center' : 10,<br>
<br>
If none of these are suitable, loc can be a 2-tuple giving x,y<br>
in axes coords, ie,<br>
<br>
loc = 0, 1 is left top<br>
loc = 0.5, 0.5 is center, center<br>
<br>
and so on. The following kwargs are supported:<br>
<br>
isaxes=True # whether this is an axes legend<br>
numpoints = 4 # the number of points in the legend line<br>
prop = FontProperties(size='smaller') # the font property<br>
pad = 0.2 # the fractional whitespace inside the legend border<br>
markerscale = 0.6 # the relative size of legend markers vs. original<br>
shadow # if True, draw a shadow behind legend<br>
labelsep = 0.005 # the vertical space between the legend entries<br>
handlelen = 0.05 # the length of the legend lines<br>
handletextsep = 0.02 # the space between the legend line and legend text<br>
axespad = 0.02 # the border between the axes and legend edge</tt></dd></dl>
<dl><dt><a name="Subplot-loglog"><strong>loglog</strong></a>(self, *args, **kwargs)</dt><dd><tt>LOGLOG(*args, **kwargs)<br>
Make a loglog plot with log scaling on the a and y axis. The args<br>
to semilog x are the same as the args to plot. See help plot for<br>
more info.<br>
Optional keyword args supported are any of the kwargs<br>
supported by plot or set_xscale or set_yscale. Notable, for<br>
log scaling:<br>
* basex: base of the x logarithm<br>
* subsx: the location of the minor ticks; None defaults to<br>
autosubs, which depend on the number of decades in the<br>
plot; see set_xscale for details<br>
* basey: base of the y logarithm<br>
* subsy: the location of the minor yticks; None defaults to<br>
autosubs, which depend on the number of decades in the<br>
plot; see set_yscale for details<br>
The remaining valid kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-matshow"><strong>matshow</strong></a>(self, Z, **kwargs)</dt><dd><tt>Plot a matrix as an image.<br>
<br>
The matrix will be shown the way it would be printed,<br>
with the first row at the top. Row and column numbering<br>
is zero-based.<br>
<br>
Argument:<br>
Z anything that can be interpreted as a 2-D array<br>
<br>
kwargs: all are passed to imshow. matshow sets defaults<br>
for extent, origin, interpolation, and aspect; use care<br>
in overriding the extent and origin kwargs, because they<br>
interact. (Also, if you want to change them, you probably<br>
should be using imshow directly in your own version of<br>
matshow.)<br>
<br>
Returns: an AxesImage instance</tt></dd></dl>
<dl><dt><a name="Subplot-panx"><strong>panx</strong></a>(self, numsteps)</dt><dd><tt>Pan the x axis numsteps (plus pan right, minus pan left)</tt></dd></dl>
<dl><dt><a name="Subplot-pany"><strong>pany</strong></a>(self, numsteps)</dt><dd><tt>Pan the x axis numsteps (plus pan up, minus pan down)</tt></dd></dl>
<dl><dt><a name="Subplot-pcolor"><strong>pcolor</strong></a>(self, *args, **kwargs)</dt><dd><tt><a href="#Subplot-pcolor">pcolor</a>(*args, **kwargs): pseudocolor plot of a 2-D array<br>
Function signatures<br>
<a href="#Subplot-pcolor">pcolor</a>(C, **kwargs)<br>
<a href="#Subplot-pcolor">pcolor</a>(X, Y, C, **kwargs)<br>
C is the array of color values<br>
X and Y, if given, specify the (x,y) coordinates of the colored<br>
quadrilaterals; the quadrilateral for C[i,j] has corners at<br>
(X[i,j],Y[i,j]), (X[i,j+1],Y[i,j+1]), (X[i+1,j],Y[i+1,j]),<br>
(X[i+1,j+1],Y[i+1,j+1]). Ideally the dimensions of X and Y<br>
should be one greater than those of C; if the dimensions are the<br>
same, then the last row and column of C will be ignored.<br>
Note that the the column index corresponds to the x-coordinate,<br>
and the row index corresponds to y; for details, see<br>
the "Grid Orientation" section below.<br>
If either or both of X and Y are 1-D arrays or column vectors,<br>
they will be expanded as needed into the appropriate 2-D arrays,<br>
making a rectangular grid.<br>
X,Y and C may be masked arrays. If either C[i,j], or one<br>
of the vertices surrounding C[i,j] (X or Y at [i,j],[i+1,j],<br>
[i,j+1],[i=1,j+1]) is masked, nothing is plotted.<br>
Optional keyword args are shown with their defaults below (you must<br>
use kwargs for these):<br>
* cmap = cm.jet : a cm Colormap instance from matplotlib.cm.<br>
defaults to cm.jet<br>
* norm = Normalize() : matplotlib.colors.Normalize instance<br>
is used to scale luminance data to 0,1.<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used. If you pass a norm<br>
instance, vmin and vmax will be None<br>
* shading = 'flat' : or 'faceted'. If 'faceted', a black grid is<br>
drawn around each rectangle; if 'flat', edges are not drawn<br>
* alpha=1.0 : the alpha blending value<br>
Return value is a matplotlib.collections.PatchCollection<br>
object<br>
Grid Orientation<br>
The orientation follows the Matlab(TM) convention: an<br>
array C with shape (nrows, ncolumns) is plotted with<br>
the column number as X and the row number as Y, increasing<br>
up; hence it is plotted the way the array would be printed,<br>
except that the Y axis is reversed. That is, C is taken<br>
as C(y,x).<br>
Similarly for meshgrid:<br>
x = arange(5)<br>
y = arange(3)<br>
X, Y = meshgrid(x,y)<br>
is equivalent to<br>
X = array([[0, 1, 2, 3, 4],<br>
[0, 1, 2, 3, 4],<br>
[0, 1, 2, 3, 4]])<br>
Y = array([[0, 0, 0, 0, 0],<br>
[1, 1, 1, 1, 1],<br>
[2, 2, 2, 2, 2]])<br>
so if you have<br>
C = rand( len(x), len(y))<br>
then you need<br>
<a href="#Subplot-pcolor">pcolor</a>(X, Y, transpose(C))<br>
or<br>
<a href="#Subplot-pcolor">pcolor</a>(transpose(C))<br>
Dimensions<br>
Matlab pcolor always discards<br>
the last row and column of C, but matplotlib displays<br>
the last row and column if X and Y are not specified, or<br>
if X and Y have one more row and column than C.<br>
kwargs can be used to control the PolyCollection properties:<br>
alpha: float<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
edgecolor: matplotlib color arg or sequence of rgba tuples<br>
facecolor: matplotlib color arg or sequence of rgba tuples<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-pcolor_classic"><strong>pcolor_classic</strong></a>(self, *args)</dt><dd><tt>pcolor_classic is no longer available; please use pcolor,<br>
which is a drop-in replacement.</tt></dd></dl>
<dl><dt><a name="Subplot-pcolormesh"><strong>pcolormesh</strong></a>(self, *args, **kwargs)</dt><dd><tt>PCOLORMESH(*args, **kwargs)<br>
Function signatures<br>
PCOLORMESH(C) - make a pseudocolor plot of matrix C<br>
PCOLORMESH(X, Y, C) - a pseudo color plot of C on the matrices X and Y<br>
PCOLORMESH(C, **kwargs) - Use keyword args to control colormapping and<br>
scaling; see below<br>
C may be a masked array, but X and Y may not. Masked array support<br>
is implemented via cmap and norm; in contrast, pcolor simply does<br>
not draw quadrilaterals with masked colors or vertices.<br>
Optional keyword args are shown with their defaults below (you must<br>
use kwargs for these):<br>
* cmap = cm.jet : a cm Colormap instance from matplotlib.cm.<br>
defaults to cm.jet<br>
* norm = Normalize() : matplotlib.colors.Normalize instance<br>
is used to scale luminance data to 0,1. Instantiate it<br>
with clip=False if C is a masked array.<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used.<br>
* shading = 'flat' : or 'faceted'. If 'faceted', a black grid is<br>
drawn around each rectangle; if 'flat', edge colors are same as<br>
face colors<br>
* alpha=1.0 : the alpha blending value<br>
Return value is a matplotlib.collections.PatchCollection<br>
object<br>
See pcolor for an explantion of the grid orientation and the<br>
expansion of 1-D X and/or Y to 2-D arrays.<br>
kwargs can be used to control the QuadMesh polygon collection properties:<br>
alpha: float<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
edgecolor: matplotlib color arg or sequence of rgba tuples<br>
facecolor: matplotlib color arg or sequence of rgba tuples<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-pick"><strong>pick</strong></a>(self, *args)</dt><dd><tt><a href="#Subplot-pick">pick</a>(mouseevent)<br>
<br>
each child artist will fire a pick event if mouseevent is over<br>
the artist and the artist has picker set</tt></dd></dl>
<dl><dt><a name="Subplot-pie"><strong>pie</strong></a>(self, x, explode<font color="#909090">=None</font>, labels<font color="#909090">=None</font>, colors<font color="#909090">=None</font>, autopct<font color="#909090">=None</font>, pctdistance<font color="#909090">=0.59999999999999998</font>, shadow<font color="#909090">=False</font>)</dt><dd><tt>PIE(x, explode=None, labels=None,<br>
colors=('b', 'g', 'r', 'c', 'm', 'y', 'k', 'w'),<br>
autopct=None, pctdistance=0.6, shadow=False)<br>
<br>
Make a pie chart of array x. The fractional area of each wedge is<br>
given by x/sum(x). If sum(x)<=1, then the values of x give the<br>
fractional area directly and the array will not be normalized.<br>
<br>
- explode, if not None, is a len(x) array which specifies the<br>
fraction of the radius to offset that wedge.<br>
<br>
- colors is a sequence of matplotlib color args that the pie chart<br>
will cycle.<br>
<br>
- labels, if not None, is a len(x) list of labels.<br>
<br>
- autopct, if not None, is a string or function used to label the<br>
wedges with their numeric value. The label will be placed inside<br>
the wedge. If it is a format string, the label will be fmt%pct.<br>
If it is a function, it will be called<br>
<br>
- pctdistance is the ratio between the center of each pie slice<br>
and the start of the text generated by autopct. Ignored if autopct<br>
is None; default is 0.6.<br>
<br>
- shadow, if True, will draw a shadow beneath the pie.<br>
<br>
The pie chart will probably look best if the figure and axes are<br>
square. Eg,<br>
<br>
figure(figsize=(8,8))<br>
ax = axes([0.1, 0.1, 0.8, 0.8])<br>
<br>
Return value:<br>
<br>
If autopct is None, return a list of (patches, texts), where patches<br>
is a sequence of matplotlib.patches.Wedge instances and texts is a<br>
list of the label Text instnaces<br>
<br>
If autopct is not None, return (patches, texts, autotexts), where<br>
patches and texts are as above, and autotexts is a list of text<br>
instances for the numeric labels</tt></dd></dl>
<dl><dt><a name="Subplot-plot"><strong>plot</strong></a>(self, *args, **kwargs)</dt><dd><tt>PLOT(*args, **kwargs)<br>
Plot lines and/or markers to the <a href="#Axes">Axes</a>. *args is a variable length<br>
argument, allowing for multiple x,y pairs with an optional format<br>
string. For example, each of the following is legal<br>
<a href="#Subplot-plot">plot</a>(x,y) # plot x and y using the default line style and color<br>
<a href="#Subplot-plot">plot</a>(x,y, 'bo') # plot x and y using blue circle markers<br>
<a href="#Subplot-plot">plot</a>(y) # plot y using x as index array 0..N-1<br>
<a href="#Subplot-plot">plot</a>(y, 'r+') # ditto, but with red plusses<br>
If x and/or y is 2-Dimensional, then the corresponding columns<br>
will be plotted.<br>
An arbitrary number of x, y, fmt groups can be specified, as in<br>
a.<a href="#Subplot-plot">plot</a>(x1, y1, 'g^', x2, y2, 'g-')<br>
Return value is a list of lines that were added.<br>
The following line styles are supported:<br>
- : solid line<br>
-- : dashed line<br>
-. : dash-dot line<br>
: : dotted line<br>
. : points<br>
, : pixels<br>
o : circle symbols<br>
^ : triangle up symbols<br>
v : triangle down symbols<br>
< : triangle left symbols<br>
> : triangle right symbols<br>
s : square symbols<br>
+ : plus symbols<br>
x : cross symbols<br>
D : diamond symbols<br>
d : thin diamond symbols<br>
1 : tripod down symbols<br>
2 : tripod up symbols<br>
3 : tripod left symbols<br>
4 : tripod right symbols<br>
h : hexagon symbols<br>
H : rotated hexagon symbols<br>
p : pentagon symbols<br>
| : vertical line symbols<br>
_ : horizontal line symbols<br>
steps : use gnuplot style 'steps' # kwarg only<br>
The following color abbreviations are supported<br>
b : blue<br>
g : green<br>
r : red<br>
c : cyan<br>
m : magenta<br>
y : yellow<br>
k : black<br>
w : white<br>
In addition, you can specify colors in many weird and<br>
wonderful ways, including full names 'green', hex strings<br>
'#008000', RGB or RGBA tuples (0,1,0,1) or grayscale<br>
intensities as a string '0.8'.<br>
Line styles and colors are combined in a single format string, as in<br>
'bo' for blue circles.<br>
The **kwargs can be used to set line properties (any property that has<br>
a set_* method). You can use this to set a line label (for auto<br>
legends), linewidth, anitialising, marker face color, etc. Here is an<br>
example:<br>
<a href="#Subplot-plot">plot</a>([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2)<br>
<a href="#Subplot-plot">plot</a>([1,2,3], [1,4,9], 'rs', label='line 2')<br>
<a href="#Subplot-axis">axis</a>([0, 4, 0, 10])<br>
<a href="#Subplot-legend">legend</a>()<br>
If you make multiple lines with one plot command, the kwargs apply<br>
to all those lines, eg<br>
<a href="#Subplot-plot">plot</a>(x1, y1, x2, y2, antialised=False)<br>
Neither line will be antialiased.<br>
The kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number<br>
kwargs scalex and scaley, if defined, are passed on<br>
to autoscale_view to determine whether the x and y axes are<br>
autoscaled; default True. See <a href="#Axes">Axes</a>.autoscale_view for more<br>
information</tt></dd></dl>
<dl><dt><a name="Subplot-plot_date"><strong>plot_date</strong></a>(self, x, y, fmt<font color="#909090">='bo'</font>, tz<font color="#909090">=None</font>, xdate<font color="#909090">=True</font>, ydate<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>PLOT_DATE(x, y, fmt='bo', tz=None, xdate=True, ydate=False, **kwargs)<br>
Similar to the <a href="#Subplot-plot">plot</a>() command, except the x or y (or both) data<br>
is considered to be dates, and the axis is labeled accordingly.<br>
x or y (or both) can be a sequence of dates represented as<br>
float days since 0001-01-01 UTC.<br>
fmt is a plot format string.<br>
tz is the time zone to use in labelling dates. Defaults to rc value.<br>
If xdate is True, the x-axis will be labeled with dates.<br>
If ydate is True, the y-axis will be labeled with dates.<br>
Note if you are using custom date tickers and formatters, it<br>
may be necessary to set the formatters/locators after the call<br>
to plot_date since plot_date will set the default tick locator<br>
to AutoDateLocator (if the tick locator is not already set to<br>
a DateLocator instance) and the default tick formatter to<br>
AutoDateFormatter (if the tick formatter is not already set to<br>
a DateFormatter instance).<br>
Valid kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number<br>
See matplotlib.dates for helper functions date2num, num2date<br>
and drange for help on creating the required floating point dates</tt></dd></dl>
<dl><dt><a name="Subplot-psd"><strong>psd</strong></a>(self, x, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, window<font color="#909090">=<function window_hanning at 0xb5bc7764></font>, noverlap<font color="#909090">=0</font>, **kwargs)</dt><dd><tt>PSD(x, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=0, **kwargs)<br>
The power spectral density by Welches average periodogram method. The<br>
vector x is divided into NFFT length segments. Each segment is<br>
detrended by function detrend and windowed by function window.<br>
noperlap gives the length of the overlap between segments. The<br>
absolute(fft(segment))**2 of each segment are averaged to compute Pxx,<br>
with a scaling to correct for power loss due to windowing. Fs is the<br>
sampling frequency.<br>
NFFT is the length of the fft segment; must be a power of 2<br>
Fs is the sampling frequency.<br>
detrend - the function applied to each segment before fft-ing,<br>
designed to remove the mean or linear trend. Unlike in matlab,<br>
where the detrend parameter is a vector, in matplotlib is it a<br>
function. The mlab module defines detrend_none, detrend_mean,<br>
detrend_linear, but you can use a custom function as well.<br>
window - the function used to window the segments. window is a<br>
function, unlike in matlab(TM) where it is a vector. mlab defines<br>
window_none, window_hanning, but you can use a custom function<br>
as well.<br>
noverlap gives the length of the overlap between segments.<br>
Returns the tuple Pxx, freqs<br>
For plotting, the power is plotted as 10*log10(pxx)) for decibels,<br>
though pxx itself is returned<br>
Refs:<br>
Bendat & Piersol -- Random Data: Analysis and Measurement<br>
Procedures, John Wiley & Sons (1986)<br>
kwargs control the Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-quiver"><strong>quiver</strong></a>(self, *args, **kw)</dt><dd><tt>Plot a 2-D field of arrows.<br>
<br>
Function signatures:<br>
<br>
<a href="#Subplot-quiver">quiver</a>(U, V, **kw)<br>
<a href="#Subplot-quiver">quiver</a>(U, V, C, **kw)<br>
<a href="#Subplot-quiver">quiver</a>(X, Y, U, V, **kw)<br>
<a href="#Subplot-quiver">quiver</a>(X, Y, U, V, C, **kw)<br>
<br>
Arguments:<br>
<br>
X, Y give the x and y coordinates of the arrow locations<br>
(default is tail of arrow; see 'pivot' kwarg)<br>
U, V give the x and y components of the arrow vectors<br>
C is an optional array used to map colors to the arrows<br>
<br>
All arguments may be 1-D or 2-D arrays or sequences.<br>
If X and Y are absent, they will be generated as a uniform grid.<br>
If U and V are 2-D arrays but X and Y are 1-D, and if<br>
len(X) and len(Y) match the column and row dimensions<br>
of U, then X and Y will be expanded with meshgrid.<br>
<br>
Keyword arguments (default given first):<br>
<br>
* units = 'width' | 'height' | 'dots' | 'inches' | 'x' | 'y'<br>
arrow units; the arrow dimensions *except for length*<br>
are in multiples of this unit.<br>
* scale = None | float<br>
data units per arrow unit, e.g. m/s per plot width;<br>
a smaller scale parameter makes the arrow longer.<br>
If None, a simple autoscaling algorithm is used, based<br>
on the average vector length and the number of vectors.<br>
<br>
Arrow dimensions and scales can be in any of several units:<br>
<br>
'width' or 'height': the width or height of the axes<br>
'dots' or 'inches': pixels or inches, based on the figure dpi<br>
'x' or 'y': X or Y data units<br>
<br>
In all cases the arrow aspect ratio is 1, so that if U==V the angle<br>
of the arrow on the plot is 45 degrees CCW from the X-axis.<br>
<br>
The arrows scale differently depending on the units, however.<br>
For 'x' or 'y', the arrows get larger as one zooms in; for other<br>
units, the arrow size is independent of the zoom state. For<br>
'width or 'height', the arrow size increases with the width and<br>
height of the axes, respectively, when the the window is resized;<br>
for 'dots' or 'inches', resizing does not change the arrows.<br>
<br>
<br>
* width = ? shaft width in arrow units; default depends on<br>
choice of units, above, and number of vectors;<br>
a typical starting value is about<br>
0.005 times the width of the plot.<br>
* headwidth = 3 head width as multiple of shaft width<br>
* headlength = 5 head length as multiple of shaft width<br>
* headaxislength = 4.5 head length at shaft intersection<br>
* minshaft = 1 length below which arrow scales, in units<br>
of head length. Do not set this to less<br>
than 1, or small arrows will look terrible!<br>
* minlength = 1 minimum length as a multiple of shaft width;<br>
if an arrow length is less than this, plot a<br>
dot (hexagon) of this diameter instead.<br>
<br>
The defaults give a slightly swept-back arrow; to make the<br>
head a triangle, make headaxislength the same as headlength.<br>
To make the arrow more pointed, reduce headwidth or increase<br>
headlength and headaxislength.<br>
To make the head smaller relative to the shaft, scale down<br>
all the head* parameters.<br>
You will probably do best to leave minshaft alone.<br>
<br>
* pivot = 'tail' | 'middle' | 'tip'<br>
The part of the arrow that is at the grid point; the arrow<br>
rotates about this point, hence the name 'pivot'.<br>
<br>
* color = 'k' | any matplotlib color spec or sequence of color specs.<br>
This is a synonym for the PolyCollection facecolor kwarg.<br>
If C has been set, 'color' has no effect.<br>
<br>
* All PolyCollection kwargs are valid, in the sense that they<br>
will be passed on to the PolyCollection constructor.<br>
In particular, one might want to use, for example:<br>
linewidths = (1,), edgecolors = ('g',)<br>
to make the arrows have green outlines of unit width.</tt></dd></dl>
<dl><dt><a name="Subplot-quiver2"><strong>quiver2</strong></a>(self, *args, **kw)</dt><dd><tt>Plot a 2-D field of arrows.<br>
<br>
Function signatures:<br>
<br>
<a href="#Subplot-quiver">quiver</a>(U, V, **kw)<br>
<a href="#Subplot-quiver">quiver</a>(U, V, C, **kw)<br>
<a href="#Subplot-quiver">quiver</a>(X, Y, U, V, **kw)<br>
<a href="#Subplot-quiver">quiver</a>(X, Y, U, V, C, **kw)<br>
<br>
Arguments:<br>
<br>
X, Y give the x and y coordinates of the arrow locations<br>
(default is tail of arrow; see 'pivot' kwarg)<br>
U, V give the x and y components of the arrow vectors<br>
C is an optional array used to map colors to the arrows<br>
<br>
All arguments may be 1-D or 2-D arrays or sequences.<br>
If X and Y are absent, they will be generated as a uniform grid.<br>
If U and V are 2-D arrays but X and Y are 1-D, and if<br>
len(X) and len(Y) match the column and row dimensions<br>
of U, then X and Y will be expanded with meshgrid.<br>
<br>
Keyword arguments (default given first):<br>
<br>
* units = 'width' | 'height' | 'dots' | 'inches' | 'x' | 'y'<br>
arrow units; the arrow dimensions *except for length*<br>
are in multiples of this unit.<br>
* scale = None | float<br>
data units per arrow unit, e.g. m/s per plot width;<br>
a smaller scale parameter makes the arrow longer.<br>
If None, a simple autoscaling algorithm is used, based<br>
on the average vector length and the number of vectors.<br>
<br>
Arrow dimensions and scales can be in any of several units:<br>
<br>
'width' or 'height': the width or height of the axes<br>
'dots' or 'inches': pixels or inches, based on the figure dpi<br>
'x' or 'y': X or Y data units<br>
<br>
In all cases the arrow aspect ratio is 1, so that if U==V the angle<br>
of the arrow on the plot is 45 degrees CCW from the X-axis.<br>
<br>
The arrows scale differently depending on the units, however.<br>
For 'x' or 'y', the arrows get larger as one zooms in; for other<br>
units, the arrow size is independent of the zoom state. For<br>
'width or 'height', the arrow size increases with the width and<br>
height of the axes, respectively, when the the window is resized;<br>
for 'dots' or 'inches', resizing does not change the arrows.<br>
<br>
<br>
* width = ? shaft width in arrow units; default depends on<br>
choice of units, above, and number of vectors;<br>
a typical starting value is about<br>
0.005 times the width of the plot.<br>
* headwidth = 3 head width as multiple of shaft width<br>
* headlength = 5 head length as multiple of shaft width<br>
* headaxislength = 4.5 head length at shaft intersection<br>
* minshaft = 1 length below which arrow scales, in units<br>
of head length. Do not set this to less<br>
than 1, or small arrows will look terrible!<br>
* minlength = 1 minimum length as a multiple of shaft width;<br>
if an arrow length is less than this, plot a<br>
dot (hexagon) of this diameter instead.<br>
<br>
The defaults give a slightly swept-back arrow; to make the<br>
head a triangle, make headaxislength the same as headlength.<br>
To make the arrow more pointed, reduce headwidth or increase<br>
headlength and headaxislength.<br>
To make the head smaller relative to the shaft, scale down<br>
all the head* parameters.<br>
You will probably do best to leave minshaft alone.<br>
<br>
* pivot = 'tail' | 'middle' | 'tip'<br>
The part of the arrow that is at the grid point; the arrow<br>
rotates about this point, hence the name 'pivot'.<br>
<br>
* color = 'k' | any matplotlib color spec or sequence of color specs.<br>
This is a synonym for the PolyCollection facecolor kwarg.<br>
If C has been set, 'color' has no effect.<br>
<br>
* All PolyCollection kwargs are valid, in the sense that they<br>
will be passed on to the PolyCollection constructor.<br>
In particular, one might want to use, for example:<br>
linewidths = (1,), edgecolors = ('g',)<br>
to make the arrows have green outlines of unit width.</tt></dd></dl>
<dl><dt><a name="Subplot-quiver_classic"><strong>quiver_classic</strong></a>(self, U, V, *args, **kwargs)</dt><dd><tt>QUIVER( X, Y, U, V )<br>
QUIVER( U, V )<br>
QUIVER( X, Y, U, V, S)<br>
QUIVER( U, V, S )<br>
QUIVER( ..., color=None, width=1.0, cmap=None, norm=None )<br>
<br>
Make a vector plot (U, V) with arrows on a grid (X, Y)<br>
<br>
If X and Y are not specified, U and V must be 2D arrays. Equally spaced<br>
X and Y grids are then generated using the meshgrid command.<br>
<br>
color can be a color value or an array of colors, so that the arrows can be<br>
colored according to another dataset. If cmap is specified and color is 'length',<br>
the colormap is used to give a color according to the vector's length.<br>
<br>
If color is a scalar field, the colormap is used to map the scalar to a color<br>
If a colormap is specified and color is an array of color triplets, then the<br>
colormap is ignored<br>
<br>
width is a scalar that controls the width of the arrows<br>
<br>
if S is specified it is used to scale the vectors. Use S=0 to disable automatic<br>
scaling.<br>
If S!=0, vectors are scaled to fit within the grid and then are multiplied by S.</tt></dd></dl>
<dl><dt><a name="Subplot-quiverkey"><strong>quiverkey</strong></a>(self, *args, **kw)</dt><dd><tt>Add a key to a quiver plot.<br>
<br>
Function signature:<br>
<a href="#Subplot-quiverkey">quiverkey</a>(Q, X, Y, U, label, **kw)<br>
<br>
Arguments:<br>
Q is the Quiver instance returned by a call to quiver.<br>
X, Y give the location of the key; additional explanation follows.<br>
U is the length of the key<br>
label is a string with the length and units of the key<br>
<br>
Keyword arguments (default given first):<br>
* coordinates = 'axes' | 'figure' | 'data' | 'inches'<br>
Coordinate system and units for X, Y: 'axes' and 'figure'<br>
are normalized coordinate systems with 0,0 in the lower<br>
left and 1,1 in the upper right; 'data' are the axes<br>
data coordinates (used for the locations of the vectors<br>
in the quiver plot itself); 'inches' is position in the<br>
figure in inches, with 0,0 at the lower left corner.<br>
* color overrides face and edge colors from Q.<br>
* labelpos = 'N' | 'S' | 'E' | 'W'<br>
Position the label above, below, to the right, to the left<br>
of the arrow, respectively.<br>
* labelsep = 0.1 inches distance between the arrow and the label<br>
* labelcolor (defaults to default Text color)<br>
* fontproperties is a dictionary with keyword arguments accepted<br>
by the FontProperties initializer: family, style, variant,<br>
size, weight<br>
<br>
Any additional keyword arguments are used to override vector<br>
properties taken from Q.<br>
<br>
The positioning of the key depends on X, Y, coordinates, and<br>
labelpos. If labelpos is 'N' or 'S', X,Y give the position<br>
of the middle of the key arrow. If labelpos is 'E', X,Y<br>
positions the head, and if labelpos is 'W', X,Y positions the<br>
tail; in either of these two cases, X,Y is somewhere in the middle<br>
of the arrow+label key object.</tt></dd></dl>
<dl><dt><a name="Subplot-redraw_in_frame"><strong>redraw_in_frame</strong></a>(self)</dt><dd><tt>This method can only be used after an initial draw which<br>
caches the renderer. It is used to efficiently update <a href="#Axes">Axes</a><br>
data (axis ticks, labels, etc are not updated)</tt></dd></dl>
<dl><dt><a name="Subplot-relim"><strong>relim</strong></a>(self)</dt><dd><tt>recompute the datalimits based on current artists</tt></dd></dl>
<dl><dt><a name="Subplot-scatter"><strong>scatter</strong></a>(self, x, y, s<font color="#909090">=20</font>, c<font color="#909090">='b'</font>, marker<font color="#909090">='o'</font>, cmap<font color="#909090">=None</font>, norm<font color="#909090">=None</font>, vmin<font color="#909090">=None</font>, vmax<font color="#909090">=None</font>, alpha<font color="#909090">=1.0</font>, linewidths<font color="#909090">=None</font>, faceted<font color="#909090">=True</font>, verts<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SCATTER(x, y, s=20, c='b', marker='o', cmap=None, norm=None,<br>
vmin=None, vmax=None, alpha=1.0, linewidths=None,<br>
faceted=True, **kwargs)<br>
Supported function signatures:<br>
SCATTER(x, y, **kwargs)<br>
SCATTER(x, y, s, **kwargs)<br>
SCATTER(x, y, s, c, **kwargs)<br>
Make a scatter plot of x versus y, where x, y are 1-D sequences<br>
of the same length, N.<br>
Arguments s and c can also be given as kwargs; this is encouraged<br>
for readability.<br>
s is a size in points^2. It is a scalar<br>
or an array of the same length as x and y.<br>
c is a color and can be a single color format string,<br>
or a sequence of color specifications of length N,<br>
or a sequence of N numbers to be mapped to colors<br>
using the cmap and norm specified via kwargs (see below).<br>
Note that c should not be a single numeric RGB or RGBA<br>
sequence because that is indistinguishable from an array<br>
of values to be colormapped. c can be a 2-D array in which<br>
the rows are RGB or RGBA, however.<br>
The marker can be one of<br>
's' : square<br>
'o' : circle<br>
'^' : triangle up<br>
'>' : triangle right<br>
'v' : triangle down<br>
'<' : triangle left<br>
'd' : diamond<br>
'p' : pentagram<br>
'h' : hexagon<br>
'8' : octagon<br>
If marker is None and verts is not None, verts is a sequence<br>
of (x,y) vertices for a custom scatter symbol.<br>
s is a size argument in points squared.<br>
Any or all of x, y, s, and c may be masked arrays, in which<br>
case all masks will be combined and only unmasked points<br>
will be plotted.<br>
Other keyword args; the color mapping and normalization arguments will<br>
on be used if c is an array of floats<br>
* cmap = cm.jet : a colors.Colormap instance from matplotlib.cm.<br>
defaults to rc image.cmap<br>
* norm = Normalize() : matplotlib.colors.Normalize instance<br>
is used to scale luminance data to 0,1.<br>
* vmin=None and vmax=None : vmin and vmax are used in conjunction<br>
with norm to normalize luminance data. If either are None, the<br>
min and max of the color array C is used. Note if you pass a norm<br>
instance, your settings for vmin and vmax will be ignored<br>
* alpha =1.0 : the alpha value for the patches<br>
* linewidths, if None, defaults to (lines.linewidth,). Note<br>
that this is a tuple, and if you set the linewidths<br>
argument you must set it as a sequence of floats, as<br>
required by RegularPolyCollection -- see<br>
matplotlib.collections.RegularPolyCollection for details<br>
* faceted: if True, will use the default edgecolor for the<br>
markers. If False, will set the edgecolors to be the same<br>
as the facecolors<br>
Optional kwargs control the PatchCollection properties:<br>
alpha: float<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
edgecolor: matplotlib color arg or sequence of rgba tuples<br>
facecolor: matplotlib color arg or sequence of rgba tuples<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-scatter_classic"><strong>scatter_classic</strong></a>(self, x, y, s<font color="#909090">=None</font>, c<font color="#909090">='b'</font>)</dt><dd><tt>scatter_classic is no longer available; please use scatter.<br>
To help in porting, for comparison to the scatter docstring,<br>
here is the scatter_classic docstring:<br>
<br>
SCATTER_CLASSIC(x, y, s=None, c='b')<br>
<br>
Make a scatter plot of x versus y. s is a size (in data coords) and<br>
can be either a scalar or an array of the same length as x or y. c is<br>
a color and can be a single color format string or an length(x) array<br>
of intensities which will be mapped by the colormap jet.<br>
<br>
If size is None a default size will be used</tt></dd></dl>
<dl><dt><a name="Subplot-semilogx"><strong>semilogx</strong></a>(self, *args, **kwargs)</dt><dd><tt>SEMILOGX(*args, **kwargs)<br>
Make a semilog plot with log scaling on the x axis. The args to<br>
semilog x are the same as the args to plot. See help plot for more<br>
info.<br>
Optional keyword args supported are any of the kwargs supported by<br>
plot or set_xscale. Notable, for log scaling:<br>
* basex: base of the logarithm<br>
* subsx: the location of the minor ticks; None defaults to<br>
autosubs, which depend on the number of decades in the<br>
plot; see set_xscale for details<br>
The remaining valid kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-semilogy"><strong>semilogy</strong></a>(self, *args, **kwargs)</dt><dd><tt>SEMILOGY(*args, **kwargs):<br>
Make a semilog plot with log scaling on the y axis. The args to<br>
semilogy are the same as the args to plot. See help plot for more<br>
info.<br>
Optional keyword args supported are any of the kwargs supported by<br>
plot or set_yscale. Notable, for log scaling:<br>
* basey: base of the logarithm<br>
* subsy: a sequence of the location of the minor ticks;<br>
None defaults to autosubs, which depend on the number of<br>
decades in the plot; see set_yscale for details<br>
The remaining valid kwargs are Line2D properties:<br>
alpha: float<br>
animated: [True | False]<br>
antialiased or aa: [True | False]<br>
axes: unknown<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color or c: any matplotlib color<br>
dash_capstyle: ['butt' | 'round' | 'projecting']<br>
dash_joinstyle: ['miter' | 'round' | 'bevel']<br>
dashes: sequence of on/off ink in points<br>
data: (array xdata, array ydata)<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle or ls: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]<br>
linewidth or lw: float value in points<br>
lod: [True | False]<br>
marker: [ '+' | ',' | '.' | '1' | '2' | '3' | '4'<br>
markeredgecolor or mec: any matplotlib color<br>
markeredgewidth or mew: float value in points<br>
markerfacecolor or mfc: any matplotlib color<br>
markersize or ms: float<br>
picker: [None|float|boolean|callable]<br>
solid_capstyle: ['butt' | 'round' | 'projecting']<br>
solid_joinstyle: ['miter' | 'round' | 'bevel']<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
xdata: array<br>
ydata: array<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-set_adjustable"><strong>set_adjustable</strong></a>(self, adjustable)</dt><dd><tt>ACCEPTS: ['box' | 'datalim']</tt></dd></dl>
<dl><dt><a name="Subplot-set_anchor"><strong>set_anchor</strong></a>(self, anchor)</dt><dd><tt>ACCEPTS: ['C', 'SW', 'S', 'SE', 'E', 'NE', 'N', 'NW', 'W']</tt></dd></dl>
<dl><dt><a name="Subplot-set_aspect"><strong>set_aspect</strong></a>(self, aspect, adjustable<font color="#909090">=None</font>, anchor<font color="#909090">=None</font>)</dt><dd><tt>aspect:<br>
'auto' - automatic; fill position rectangle with data<br>
'normal' - same as 'auto'; deprecated<br>
'equal' - same scaling from data to plot units for x and y<br>
num - a circle will be stretched such that the height<br>
is num times the width. aspect=1 is the same as<br>
aspect='equal'.<br>
<br>
adjustable:<br>
'box' - change physical size of axes<br>
'datalim' - change xlim or ylim<br>
<br>
anchor:<br>
'C' - centered<br>
'SW' - lower left corner<br>
'S' - middle of bottom edge<br>
'SE' - lower right corner<br>
etc.<br>
<br>
ACCEPTS: ['auto' | 'equal' | aspect_ratio]</tt></dd></dl>
<dl><dt><a name="Subplot-set_autoscale_on"><strong>set_autoscale_on</strong></a>(self, b)</dt><dd><tt>Set whether autoscaling is applied on plot commands<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="Subplot-set_axis_bgcolor"><strong>set_axis_bgcolor</strong></a>(self, color)</dt><dd><tt>set the axes background color<br>
<br>
ACCEPTS: any matplotlib color - see help(colors)</tt></dd></dl>
<dl><dt><a name="Subplot-set_axis_off"><strong>set_axis_off</strong></a>(self)</dt><dd><tt>turn off the axis<br>
<br>
ACCEPTS: void</tt></dd></dl>
<dl><dt><a name="Subplot-set_axis_on"><strong>set_axis_on</strong></a>(self)</dt><dd><tt>turn on the axis<br>
<br>
ACCEPTS: void</tt></dd></dl>
<dl><dt><a name="Subplot-set_axisbelow"><strong>set_axisbelow</strong></a>(self, b)</dt><dd><tt>Set whether the axis ticks and gridlines are above or below most artists<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="Subplot-set_cursor_props"><strong>set_cursor_props</strong></a>(self, *args)</dt><dd><tt>Set the cursor property as<br>
ax.<a href="#Subplot-set_cursor_props">set_cursor_props</a>(linewidth, color) OR<br>
ax.<a href="#Subplot-set_cursor_props">set_cursor_props</a>((linewidth, color))<br>
<br>
ACCEPTS: a (float, color) tuple</tt></dd></dl>
<dl><dt><a name="Subplot-set_figure"><strong>set_figure</strong></a>(self, fig)</dt><dd><tt>Set the <a href="#Axes">Axes</a> figure<br>
<br>
ACCEPTS: a Figure instance</tt></dd></dl>
<dl><dt><a name="Subplot-set_frame_on"><strong>set_frame_on</strong></a>(self, b)</dt><dd><tt>Set whether the axes rectangle patch is drawn<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="Subplot-set_navigate"><strong>set_navigate</strong></a>(self, b)</dt><dd><tt>Set whether the axes responds to navigation toolbar commands<br>
<br>
ACCEPTS: True|False</tt></dd></dl>
<dl><dt><a name="Subplot-set_navigate_mode"><strong>set_navigate_mode</strong></a>(self, b)</dt><dd><tt>Set the navigation toolbar button status;<br>
this is not a user-API function.</tt></dd></dl>
<dl><dt><a name="Subplot-set_position"><strong>set_position</strong></a>(self, pos, which<font color="#909090">='both'</font>)</dt><dd><tt>Set the axes position with pos = [left, bottom, width, height]<br>
in relative 0,1 coords<br>
<br>
There are two position variables: one which is ultimately<br>
used, but which may be modified by apply_aspect, and a second<br>
which is the starting point for apply_aspect.<br>
<br>
which = 'active' to change the first;<br>
'original' to change the second;<br>
'both' to change both<br>
<br>
ACCEPTS: len(4) sequence of floats</tt></dd></dl>
<dl><dt><a name="Subplot-set_title"><strong>set_title</strong></a>(self, label, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_TITLE(label, fontdict=None, **kwargs):<br>
Set the title for the axes. See the text docstring for information<br>
of how override and the optional args work<br>
kwargs are Text properties:<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="Subplot-set_xlabel"><strong>set_xlabel</strong></a>(self, xlabel, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_XLABEL(xlabel, fontdict=None, **kwargs)<br>
Set the label for the xaxis. See the text docstring for information<br>
of how override and the optional args work.<br>
Valid kwargs are Text properties:<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="Subplot-set_xlim"><strong>set_xlim</strong></a>(self, xmin<font color="#909090">=None</font>, xmax<font color="#909090">=None</font>, emit<font color="#909090">=False</font>, **kwargs)</dt><dd><tt><a href="#Subplot-set_xlim">set_xlim</a>(self, *args, **kwargs):<br>
<br>
Set the limits for the xaxis; v = [xmin, xmax]<br>
<br>
<a href="#Subplot-set_xlim">set_xlim</a>((valmin, valmax))<br>
<a href="#Subplot-set_xlim">set_xlim</a>(valmin, valmax)<br>
<a href="#Subplot-set_xlim">set_xlim</a>(xmin=1) # xmax unchanged<br>
<a href="#Subplot-set_xlim">set_xlim</a>(xmax=1) # xmin unchanged<br>
<br>
Valid kwargs:<br>
<br>
xmin : the min of the xlim<br>
xmax : the max of the xlim<br>
emit : notify observers of lim change<br>
<br>
<br>
Returns the current xlimits as a length 2 tuple<br>
<br>
ACCEPTS: len(2) sequence of floats</tt></dd></dl>
<dl><dt><a name="Subplot-set_xscale"><strong>set_xscale</strong></a>(self, value, basex<font color="#909090">=10</font>, subsx<font color="#909090">=None</font>)</dt><dd><tt>SET_XSCALE(value, basex=10, subsx=None)<br>
<br>
Set the xscaling: 'log' or 'linear'<br>
<br>
If value is 'log', the additional kwargs have the following meaning<br>
<br>
* basex: base of the logarithm<br>
<br>
* subsx: a sequence of the location of the minor ticks;<br>
None defaults to autosubs, which depend on the number of<br>
decades in the plot. Eg for base 10, subsx=(1,2,5) will<br>
put minor ticks on 1,2,5,11,12,15,21, ....To turn off<br>
minor ticking, set subsx=[]<br>
<br>
ACCEPTS: ['log' | 'linear' ]</tt></dd></dl>
<dl><dt><a name="Subplot-set_xticklabels"><strong>set_xticklabels</strong></a>(self, labels, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_XTICKLABELS(labels, fontdict=None, **kwargs)<br>
Set the xtick labels with list of strings labels Return a list of axis<br>
text instances.<br>
kwargs set the Text properties. Valid properties are<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: sequence of strings</tt></dd></dl>
<dl><dt><a name="Subplot-set_xticks"><strong>set_xticks</strong></a>(self, ticks)</dt><dd><tt>Set the x ticks with list of ticks<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="Subplot-set_ylabel"><strong>set_ylabel</strong></a>(self, ylabel, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_YLABEL(ylabel, fontdict=None, **kwargs)<br>
Set the label for the yaxis<br>
See the text doctstring for information of how override and<br>
the optional args work<br>
Valid kwargs are Text properties:<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: str</tt></dd></dl>
<dl><dt><a name="Subplot-set_ylim"><strong>set_ylim</strong></a>(self, ymin<font color="#909090">=None</font>, ymax<font color="#909090">=None</font>, emit<font color="#909090">=False</font>, **kwargs)</dt><dd><tt><a href="#Subplot-set_ylim">set_ylim</a>(self, *args, **kwargs):<br>
<br>
Set the limits for the yaxis; v = [ymin, ymax]<br>
<br>
<a href="#Subplot-set_ylim">set_ylim</a>((valmin, valmax))<br>
<a href="#Subplot-set_ylim">set_ylim</a>(valmin, valmax)<br>
<a href="#Subplot-set_ylim">set_ylim</a>(ymin=1) # ymax unchanged<br>
<a href="#Subplot-set_ylim">set_ylim</a>(ymax=1) # ymin unchanged<br>
<br>
Valid kwargs:<br>
<br>
ymin : the min of the ylim<br>
ymax : the max of the ylim<br>
emit : notify observers of lim change<br>
<br>
Returns the current ylimits as a length 2 tuple<br>
<br>
ACCEPTS: len(2) sequence of floats</tt></dd></dl>
<dl><dt><a name="Subplot-set_yscale"><strong>set_yscale</strong></a>(self, value, basey<font color="#909090">=10</font>, subsy<font color="#909090">=None</font>)</dt><dd><tt>SET_YSCALE(value, basey=10, subsy=None)<br>
<br>
Set the yscaling: 'log' or 'linear'<br>
<br>
If value is 'log', the additional kwargs have the following meaning<br>
<br>
* basey: base of the logarithm<br>
<br>
* subsy: a sequence of the location of the minor ticks;<br>
None defaults to autosubs, which depend on the number of<br>
decades in the plot. Eg for base 10, subsy=(1,2,5) will<br>
put minor ticks on 1,2,5,11,12,15, 21, ....To turn off<br>
minor ticking, set subsy=[]<br>
<br>
ACCEPTS: ['log' | 'linear']</tt></dd></dl>
<dl><dt><a name="Subplot-set_yticklabels"><strong>set_yticklabels</strong></a>(self, labels, fontdict<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>SET_YTICKLABELS(labels, fontdict=None, **kwargs)<br>
Set the ytick labels with list of strings labels. Return a list of<br>
Text instances.<br>
kwargs set Text properties for the labels. Valid properties are<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number<br>
ACCEPTS: sequence of strings</tt></dd></dl>
<dl><dt><a name="Subplot-set_yticks"><strong>set_yticks</strong></a>(self, ticks)</dt><dd><tt>Set the y ticks with list of ticks<br>
<br>
ACCEPTS: sequence of floats</tt></dd></dl>
<dl><dt><a name="Subplot-specgram"><strong>specgram</strong></a>(self, x, NFFT<font color="#909090">=256</font>, Fs<font color="#909090">=2</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, window<font color="#909090">=<function window_hanning at 0xb5bc7764></font>, noverlap<font color="#909090">=128</font>, cmap<font color="#909090">=None</font>, xextent<font color="#909090">=None</font>)</dt><dd><tt>SPECGRAM(x, NFFT=256, Fs=2, detrend=detrend_none,<br>
window=window_hanning, noverlap=128,<br>
cmap=None, xextent=None)<br>
<br>
Compute a spectrogram of data in x. Data are split into NFFT length<br>
segements and the PSD of each section is computed. The windowing<br>
function window is applied to each segment, and the amount of overlap<br>
of each segment is specified with noverlap.<br>
<br>
* cmap is a colormap; if None use default determined by rc<br>
<br>
* xextent is the image extent in the xaxes xextent=xmin, xmax -<br>
default 0, max(bins), 0, max(freqs) where bins is the return<br>
value from matplotlib.matplotlib.mlab.specgram<br>
<br>
* See help(psd) for information on the other keyword arguments.<br>
<br>
Return value is (Pxx, freqs, bins, im), where<br>
<br>
bins are the time points the spectrogram is calculated over<br>
<br>
freqs is an array of frequencies<br>
<br>
Pxx is a len(times) x len(freqs) array of power<br>
<br>
im is a matplotlib.image.AxesImage.<br>
<br>
Note: If x is real (i.e. non-complex) only the positive spectrum is<br>
shown. If x is complex both positive and negative parts of the<br>
spectrum are shown.</tt></dd></dl>
<dl><dt><a name="Subplot-spy"><strong>spy</strong></a>(self, Z, precision<font color="#909090">=None</font>, marker<font color="#909090">=None</font>, markersize<font color="#909090">=None</font>, aspect<font color="#909090">='equal'</font>, **kwargs)</dt><dd><tt><a href="#Subplot-spy">spy</a>(Z) plots the sparsity pattern of the 2-D array Z<br>
<br>
If precision is None, any non-zero value will be plotted;<br>
else, values of absolute(Z)>precision will be plotted.<br>
<br>
The array will be plotted as it would be printed, with<br>
the first index (row) increasing down and the second<br>
index (column) increasing to the right.<br>
<br>
By default aspect is 'equal' so that each array element<br>
occupies a square space; set the aspect kwarg to 'auto'<br>
to allow the plot to fill the plot box, or to any scalar<br>
number to specify the aspect ratio of an array element<br>
directly.<br>
<br>
Two plotting styles are available: image or marker. Both<br>
are available for full arrays, but only the marker style<br>
works for scipy.sparse.spmatrix instances.<br>
<br>
If marker and markersize are None, an image will be<br>
returned and any remaining kwargs are passed to imshow;<br>
else, a Line2D object will be returned with the value<br>
of marker determining the marker type, and any remaining<br>
kwargs passed to the axes plot method.<br>
<br>
If marker and markersize are None, useful kwargs include:<br>
cmap<br>
alpha<br>
See documentation for <a href="#Subplot-imshow">imshow</a>() for details.<br>
For controlling colors, e.g. cyan background and red marks, use:<br>
cmap = matplotlib.colors.ListedColormap(['c','r'])<br>
<br>
If marker or markersize is not None, useful kwargs include:<br>
marker<br>
markersize<br>
color<br>
See documentation for <a href="#Subplot-plot">plot</a>() for details.<br>
<br>
Useful values for marker include:<br>
's' square (default)<br>
'o' circle<br>
'.' point<br>
',' pixel</tt></dd></dl>
<dl><dt><a name="Subplot-stem"><strong>stem</strong></a>(self, x, y, linefmt<font color="#909090">='b-'</font>, markerfmt<font color="#909090">='bo'</font>, basefmt<font color="#909090">='r-'</font>)</dt><dd><tt>STEM(x, y, linefmt='b-', markerfmt='bo', basefmt='r-')<br>
<br>
A stem plot plots vertical lines (using linefmt) at each x location<br>
from the baseline to y, and places a marker there using markerfmt. A<br>
horizontal line at 0 is is plotted using basefmt<br>
<br>
Return value is (markerline, stemlines, baseline) .<br>
<br>
See<br>
<a href="http://www.mathworks.com/access/helpdesk/help/techdoc/ref/stem.html">http://www.mathworks.com/access/helpdesk/help/techdoc/ref/stem.html</a><br>
for details and examples/stem_plot.py for a demo.</tt></dd></dl>
<dl><dt><a name="Subplot-table"><strong>table</strong></a>(self, **kwargs)</dt><dd><tt>TABLE(cellText=None, cellColours=None,<br>
cellLoc='right', colWidths=None,<br>
rowLabels=None, rowColours=None, rowLoc='left',<br>
colLabels=None, colColours=None, colLoc='center',<br>
loc='bottom', bbox=None):<br>
Add a table to the current axes. Returns a table instance. For<br>
finer grained control over tables, use the Table class and add it<br>
to the axes with add_table.<br>
Thanks to John Gill for providing the class and table.<br>
kwargs control the Table properties:<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
figure: a matplotlib.figure.Figure instance<br>
fontsize: a float in points<br>
label: any string<br>
lod: [True | False]<br>
picker: [None|float|boolean|callable]<br>
transform: a matplotlib.transform transformation instance<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-text"><strong>text</strong></a>(self, x, y, s, fontdict<font color="#909090">=None</font>, withdash<font color="#909090">=False</font>, **kwargs)</dt><dd><tt>TEXT(x, y, s, fontdict=None, **kwargs)<br>
Add text in string s to axis at location x,y (data coords)<br>
fontdict is a dictionary to override the default text properties.<br>
If fontdict is None, the defaults are determined by your rc<br>
parameters.<br>
withdash=True will create a TextWithDash instance instead<br>
of a Text instance.<br>
Individual keyword arguments can be used to override any given<br>
parameter<br>
<a href="#Subplot-text">text</a>(x, y, s, fontsize=12)<br>
The default transform specifies that text is in data coords,<br>
alternatively, you can specify text in axis coords (0,0 lower left and<br>
1,1 upper right). The example below places text in the center of the<br>
axes<br>
<a href="#Subplot-text">text</a>(0.5, 0.5,'matplotlib',<br>
horizontalalignment='center',<br>
verticalalignment='center',<br>
transform = ax.transAxes,<br>
)<br>
You can put a rectangular box around the text instance (eg to<br>
set a background color) by using the keyword bbox. bbox is a<br>
dictionary of matplotlib.patches.Rectangle properties (see help<br>
for Rectangle for a list of these). For example<br>
<a href="#Subplot-text">text</a>(x, y, s, bbox=dict(facecolor='red', alpha=0.5))<br>
Valid kwargs are Text properties<br>
alpha: float<br>
animated: [True | False]<br>
axes: an axes instance<br>
backgroundcolor: any matplotlib color<br>
bbox: rectangle prop dict plus key 'pad' which is a pad in points<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
color: any matplotlib color<br>
family: [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]<br>
figure: a matplotlib.figure.Figure instance<br>
fontproperties: a matplotlib.font_manager.FontProperties instance<br>
horizontalalignment or ha: [ 'center' | 'right' | 'left' ]<br>
label: any string<br>
lod: [True | False]<br>
multialignment: ['left' | 'right' | 'center' ]<br>
name or fontname: string eg, ['Sans' | 'Courier' | 'Helvetica' ...]<br>
picker: [None|float|boolean|callable]<br>
position: (x,y)<br>
rotation: [ angle in degrees 'vertical' | 'horizontal'<br>
size or fontsize: [ size in points | relative size eg 'smaller', 'x-large' ]<br>
style or fontstyle: [ 'normal' | 'italic' | 'oblique']<br>
text: string or anything printable with '%s' conversion<br>
transform: a matplotlib.transform transformation instance<br>
variant: [ 'normal' | 'small-caps' ]<br>
verticalalignment or va: [ 'center' | 'top' | 'bottom' ]<br>
visible: [True | False]<br>
weight or fontweight: [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']<br>
x: float<br>
y: float<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-ticklabel_format"><strong>ticklabel_format</strong></a>(self, **kwargs)</dt><dd><tt>Convenience method for manipulating the ScalarFormatter<br>
used by default for linear axes.<br>
<br>
kwargs:<br>
style = 'sci' (or 'scientific') or 'plain';<br>
plain turns off scientific notation<br>
axis = 'x', 'y', or 'both'<br>
<br>
Only the major ticks are affected.<br>
If the method is called when the ScalarFormatter is not<br>
the one being used, an AttributeError will be raised with<br>
no additional error message.<br>
<br>
Additional capabilities and/or friendlier error checking may be added.</tt></dd></dl>
<dl><dt><a name="Subplot-toggle_log_lineary"><strong>toggle_log_lineary</strong></a>(self)</dt><dd><tt>toggle between log and linear on the y axis</tt></dd></dl>
<dl><dt><a name="Subplot-update_datalim"><strong>update_datalim</strong></a>(self, xys)</dt><dd><tt>Update the data lim bbox with seq of xy tups or equiv. 2-D array</tt></dd></dl>
<dl><dt><a name="Subplot-update_datalim_numerix"><strong>update_datalim_numerix</strong></a>(self, x, y)</dt><dd><tt>Update the data lim bbox with seq of xy tups</tt></dd></dl>
<dl><dt><a name="Subplot-vlines"><strong>vlines</strong></a>(self, x, ymin, ymax, colors<font color="#909090">='k'</font>, linestyle<font color="#909090">='solid'</font>, label<font color="#909090">=''</font>, **kwargs)</dt><dd><tt>VLINES(x, ymin, ymax, color='k')<br>
Plot vertical lines at each x from ymin to ymax. ymin or ymax can be<br>
scalars or len(x) numpy arrays. If they are scalars, then the<br>
respective values are constant, else the heights of the lines are<br>
determined by ymin and ymax<br>
colors is a line collections color args, either a single color<br>
or a len(x) list of colors<br>
linestyle is one of solid|dashed|dashdot|dotted<br>
Returns the LineCollection that was added<br>
kwargs are LineCollection properties:<br>
alpha: float or sequence of floats<br>
animated: [True | False]<br>
array: unknown<br>
axes: an axes instance<br>
clim: a length 2 sequence of floats<br>
clip_box: a matplotlib.transform.Bbox instance<br>
clip_on: [True | False]<br>
clip_path: an agg.path_storage instance<br>
cmap: a colormap<br>
color: matplotlib color arg or sequence of rgba tuples<br>
colorbar: unknown<br>
figure: a matplotlib.figure.Figure instance<br>
label: any string<br>
linestyle: ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]<br>
linewidth: float or sequence of floats<br>
lod: [True | False]<br>
norm: unknown<br>
picker: [None|float|boolean|callable]<br>
segments: unknown<br>
transform: a matplotlib.transform transformation instance<br>
verts: unknown<br>
visible: [True | False]<br>
zorder: any number</tt></dd></dl>
<dl><dt><a name="Subplot-xaxis_date"><strong>xaxis_date</strong></a>(self, tz<font color="#909090">=None</font>)</dt><dd><tt>Sets up x-axis ticks and labels that treat the x data as dates.<br>
<br>
tz is the time zone to use in labeling dates. Defaults to rc value.</tt></dd></dl>
<dl><dt><a name="Subplot-xcorr"><strong>xcorr</strong></a>(self, x, y, normed<font color="#909090">=False</font>, detrend<font color="#909090">=<function detrend_none at 0xb5bc787c></font>, usevlines<font color="#909090">=False</font>, maxlags<font color="#909090">=None</font>, **kwargs)</dt><dd><tt>XCORR(x, y, normed=False, detrend=detrend_none, usevlines=False, **kwargs):<br>
Plot the cross correlation between x and y. If normed=True,<br>
normalize the data but the cross correlation at 0-th lag. x<br>
and y are detrended by the detrend callable (default no<br>
normalization. x and y must be equal length<br>
data are plotted as <a href="#Subplot-plot">plot</a>(lags, c, **kwargs)<br>
return value is lags, c, line where lags are a length<br>
2*maxlags+1 lag vector, c is the 2*maxlags+1 auto correlation<br>
vector, and line is a Line2D instance returned by plot. The<br>
default linestyle is None and the default marker is 'o',<br>
though these can be overridden with keyword args. The cross<br>
correlation is performed with numerix cross_correlate with<br>
mode=2.<br>
If usevlines is True, <a href="#Axes">Axes</a>.vlines rather than <a href="#Axes">Axes</a>.plot is used<br>
to draw vertical lines from the origin to the acorr.<br>
Otherwise the plotstyle is determined by the kwargs, which are<br>
Line2D properties. If usevlines, the return value is lags, c,<br>
linecol, b where linecol is the LineCollection and b is the x-axis<br>
if usevlines=True, kwargs are passed onto <a href="#Axes">Axes</a>.vlines<br>
if usevlines=False, kwargs are passed onto <a href="#Axes">Axes</a>.plot<br>
maxlags is a positive integer detailing the number of lags to show.<br>
The default value of None will return all (2*len(x)-1) lags.<br>
See the respective function for documentation on valid kwargs</tt></dd></dl>
<dl><dt><a name="Subplot-yaxis_date"><strong>yaxis_date</strong></a>(self, tz<font color="#909090">=None</font>)</dt><dd><tt>Sets up y-axis ticks and labels that treat the y data as dates.<br>
<br>
tz is the time zone to use in labeling dates. Defaults to rc value.</tt></dd></dl>
<dl><dt><a name="Subplot-zoomx"><strong>zoomx</strong></a>(self, numsteps)</dt><dd><tt>Zoom in on the x xaxis numsteps (plus for zoom in, minus for zoom out)</tt></dd></dl>
<dl><dt><a name="Subplot-zoomy"><strong>zoomy</strong></a>(self, numsteps)</dt><dd><tt>Zoom in on the x xaxis numsteps (plus for zoom in, minus for zoom out)</tt></dd></dl>
<hr>
Data and other attributes inherited from <a href="matplotlib.axes.html#Axes">Axes</a>:<br>
<dl><dt><strong>scaled</strong> = {0: 'linear', 1: 'log'}</dl>
<hr>
Methods inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><a name="Subplot-add_callback"><strong>add_callback</strong></a>(self, func)</dt></dl>
<dl><dt><a name="Subplot-convert_xunits"><strong>convert_xunits</strong></a>(self, x)</dt><dd><tt>for artists in an axes, if the xaxis as units support,<br>
convert x using xaxis unit type</tt></dd></dl>
<dl><dt><a name="Subplot-convert_yunits"><strong>convert_yunits</strong></a>(self, y)</dt><dd><tt>for artists in an axes, if the yaxis as units support,<br>
convert y using yaxis unit type</tt></dd></dl>
<dl><dt><a name="Subplot-get_alpha"><strong>get_alpha</strong></a>(self)</dt><dd><tt>Return the alpha value used for blending - not supported on all<br>
backends</tt></dd></dl>
<dl><dt><a name="Subplot-get_animated"><strong>get_animated</strong></a>(self)</dt><dd><tt>return the artist's animated state</tt></dd></dl>
<dl><dt><a name="Subplot-get_axes"><strong>get_axes</strong></a>(self)</dt><dd><tt>return the axes instance the artist resides in, or None</tt></dd></dl>
<dl><dt><a name="Subplot-get_clip_box"><strong>get_clip_box</strong></a>(self)</dt><dd><tt>Return artist clipbox</tt></dd></dl>
<dl><dt><a name="Subplot-get_clip_on"><strong>get_clip_on</strong></a>(self)</dt><dd><tt>Return whether artist uses clipping</tt></dd></dl>
<dl><dt><a name="Subplot-get_clip_path"><strong>get_clip_path</strong></a>(self)</dt><dd><tt>Return artist clip path</tt></dd></dl>
<dl><dt><a name="Subplot-get_figure"><strong>get_figure</strong></a>(self)</dt><dd><tt>return the figure instance</tt></dd></dl>
<dl><dt><a name="Subplot-get_label"><strong>get_label</strong></a>(self)</dt></dl>
<dl><dt><a name="Subplot-get_picker"><strong>get_picker</strong></a>(self)</dt><dd><tt>return the Pickeration instance used by this artist</tt></dd></dl>
<dl><dt><a name="Subplot-get_transform"><strong>get_transform</strong></a>(self)</dt><dd><tt>return the Transformation instance used by this artist</tt></dd></dl>
<dl><dt><a name="Subplot-get_visible"><strong>get_visible</strong></a>(self)</dt><dd><tt>return the artist's visiblity</tt></dd></dl>
<dl><dt><a name="Subplot-get_zorder"><strong>get_zorder</strong></a>(self)</dt></dl>
<dl><dt><a name="Subplot-have_units"><strong>have_units</strong></a>(self)</dt><dd><tt>return True if units are set on the x or y axes</tt></dd></dl>
<dl><dt><a name="Subplot-is_figure_set"><strong>is_figure_set</strong></a>(self)</dt></dl>
<dl><dt><a name="Subplot-is_transform_set"><strong>is_transform_set</strong></a>(self)</dt><dd><tt><a href="matplotlib.artist.html#Artist">Artist</a> has transform explicity let</tt></dd></dl>
<dl><dt><a name="Subplot-pchanged"><strong>pchanged</strong></a>(self)</dt><dd><tt>fire event when property changed</tt></dd></dl>
<dl><dt><a name="Subplot-pickable"><strong>pickable</strong></a>(self)</dt><dd><tt>return True if self is pickable</tt></dd></dl>
<dl><dt><a name="Subplot-remove_callback"><strong>remove_callback</strong></a>(self, oid)</dt></dl>
<dl><dt><a name="Subplot-set"><strong>set</strong></a>(self, **kwargs)</dt><dd><tt>A tkstyle set command, pass kwargs to set properties</tt></dd></dl>
<dl><dt><a name="Subplot-set_alpha"><strong>set_alpha</strong></a>(self, alpha)</dt><dd><tt>Set the alpha value used for blending - not supported on<br>
all backends<br>
<br>
ACCEPTS: float</tt></dd></dl>
<dl><dt><a name="Subplot-set_animated"><strong>set_animated</strong></a>(self, b)</dt><dd><tt>set the artist's animation state<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="Subplot-set_axes"><strong>set_axes</strong></a>(self, axes)</dt><dd><tt>set the axes instance the artist resides in, if any<br>
<br>
ACCEPTS: an axes instance</tt></dd></dl>
<dl><dt><a name="Subplot-set_clip_box"><strong>set_clip_box</strong></a>(self, clipbox)</dt><dd><tt>Set the artist's clip Bbox<br>
<br>
ACCEPTS: a matplotlib.transform.Bbox instance</tt></dd></dl>
<dl><dt><a name="Subplot-set_clip_on"><strong>set_clip_on</strong></a>(self, b)</dt><dd><tt>Set whether artist uses clipping<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="Subplot-set_clip_path"><strong>set_clip_path</strong></a>(self, path)</dt><dd><tt>Set the artist's clip path<br>
<br>
ACCEPTS: an agg.path_storage instance</tt></dd></dl>
<dl><dt><a name="Subplot-set_label"><strong>set_label</strong></a>(self, s)</dt><dd><tt>Set the line label to s for auto legend<br>
<br>
ACCEPTS: any string</tt></dd></dl>
<dl><dt><a name="Subplot-set_lod"><strong>set_lod</strong></a>(self, on)</dt><dd><tt>Set Level of Detail on or off. If on, the artists may examine<br>
things like the pixel width of the axes and draw a subset of<br>
their contents accordingly<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="Subplot-set_picker"><strong>set_picker</strong></a>(self, picker)</dt><dd><tt>set the epsilon for picking used by this artist<br>
<br>
picker can be one of the following:<br>
<br>
None - picking is disabled for this artist (default)<br>
<br>
boolean - if True then picking will be enabled and the<br>
artist will fire a pick event if the mouse event is over<br>
the artist<br>
<br>
float - if picker is a number it is interpreted as an<br>
epsilon tolerance in points and the the artist will fire<br>
off an event if it's data is within epsilon of the mouse<br>
event. For some artists like lines and patch collections,<br>
the artist may provide additional data to the pick event<br>
that is generated, eg the indices of the data within<br>
epsilon of the pick event<br>
<br>
function - if picker is callable, it is a user supplied<br>
function which determines whether the artist is hit by the<br>
mouse event.<br>
<br>
hit, props = picker(artist, mouseevent)<br>
<br>
to determine the hit test. if the mouse event is over the<br>
artist, return hit=True and props is a dictionary of<br>
properties you want added to the PickEvent attributes<br>
<br>
ACCEPTS: [None|float|boolean|callable]</tt></dd></dl>
<dl><dt><a name="Subplot-set_transform"><strong>set_transform</strong></a>(self, t)</dt><dd><tt>set the Transformation instance used by this artist<br>
<br>
ACCEPTS: a matplotlib.transform transformation instance</tt></dd></dl>
<dl><dt><a name="Subplot-set_visible"><strong>set_visible</strong></a>(self, b)</dt><dd><tt>set the artist's visiblity<br>
<br>
ACCEPTS: [True | False]</tt></dd></dl>
<dl><dt><a name="Subplot-set_zorder"><strong>set_zorder</strong></a>(self, level)</dt><dd><tt>Set the zorder for the artist<br>
<br>
ACCEPTS: any number</tt></dd></dl>
<dl><dt><a name="Subplot-update"><strong>update</strong></a>(self, props)</dt></dl>
<dl><dt><a name="Subplot-update_from"><strong>update_from</strong></a>(self, other)</dt><dd><tt>copy properties from other to self</tt></dd></dl>
<hr>
Data and other attributes inherited from <a href="matplotlib.artist.html#Artist">matplotlib.artist.Artist</a>:<br>
<dl><dt><strong>aname</strong> = 'Artist'</dl>
<dl><dt><strong>zorder</strong> = 0</dl>
</td></tr></table> <p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#ffc8d8">
<td colspan=3 valign=bottom> <br>
<font color="#000000" face="helvetica, arial"><a name="SubplotBase">class <strong>SubplotBase</strong></a></font></td></tr>
<tr bgcolor="#ffc8d8"><td rowspan=2><tt> </tt></td>
<td colspan=2><tt>Emulate matlab's(TM) subplot command, creating axes with<br>
<br>
<a href="#Subplot">Subplot</a>(numRows, numCols, plotNum)<br>
<br>
where plotNum=1 is the first plot number and increasing plotNums<br>
fill rows first. max(plotNum)==numRows*numCols<br>
<br>
You can leave out the commas if numRows<=numCols<=plotNum<10, as<br>
in<br>
<br>
<a href="#Subplot">Subplot</a>(211) # 2 rows, 1 column, first (upper) plot<br> </tt></td></tr>
<tr><td> </td>
<td width="100%">Methods defined here:<br>
<dl><dt><a name="SubplotBase-__init__"><strong>__init__</strong></a>(self, fig, *args)</dt><dd><tt>fig is a figure instance<br>
<br>
args is a varargs to specify the subplot</tt></dd></dl>
<dl><dt><a name="SubplotBase-change_geometry"><strong>change_geometry</strong></a>(self, numrows, numcols, num)</dt><dd><tt>change subplot geometry, eg from 1,1,1 to 2,2,3</tt></dd></dl>
<dl><dt><a name="SubplotBase-get_geometry"><strong>get_geometry</strong></a>(self)</dt><dd><tt>get the subplot geometry, eg 2,2,3</tt></dd></dl>
<dl><dt><a name="SubplotBase-is_first_col"><strong>is_first_col</strong></a>(self)</dt></dl>
<dl><dt><a name="SubplotBase-is_first_row"><strong>is_first_row</strong></a>(self)</dt></dl>
<dl><dt><a name="SubplotBase-is_last_col"><strong>is_last_col</strong></a>(self)</dt></dl>
<dl><dt><a name="SubplotBase-is_last_row"><strong>is_last_row</strong></a>(self)</dt></dl>
<dl><dt><a name="SubplotBase-label_outer"><strong>label_outer</strong></a>(self)</dt><dd><tt>set the visible property on ticklabels so xticklabels are<br>
visible only if the subplot is in the last row and yticklabels<br>
are visible only if the subplot is in the first column</tt></dd></dl>
<dl><dt><a name="SubplotBase-update_params"><strong>update_params</strong></a>(self)</dt><dd><tt>update the subplot position from fig.subplotpars</tt></dd></dl>
</td></tr></table></td></tr></table><p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#eeaa77">
<td colspan=3 valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"><big><strong>Functions</strong></big></font></td></tr>
<tr><td bgcolor="#eeaa77"><tt> </tt></td><td> </td>
<td width="100%"><dl><dt><a name="-Affine"><strong>Affine</strong></a>(...)</dt><dd><tt><a href="#-Affine">Affine</a>(a,b,c,d,tx,ty)</tt></dd></dl>
<dl><dt><a name="-Bbox"><strong>Bbox</strong></a>(...)</dt><dd><tt><a href="#-Bbox">Bbox</a>(ll, ur)</tt></dd></dl>
<dl><dt><a name="-Func"><strong>Func</strong></a>(...)</dt><dd><tt><a href="#-Func">Func</a>(typecode)</tt></dd></dl>
<dl><dt><a name="-FuncXY"><strong>FuncXY</strong></a>(...)</dt><dd><tt><a href="#-FuncXY">FuncXY</a>(funcx, funcy)</tt></dd></dl>
<dl><dt><a name="-Interval"><strong>Interval</strong></a>(...)</dt><dd><tt><a href="#-Interval">Interval</a>(val1, val2)</tt></dd></dl>
<dl><dt><a name="-NonseparableTransformation"><strong>NonseparableTransformation</strong></a>(...)</dt><dd><tt><a href="#-NonseparableTransformation">NonseparableTransformation</a>(box1, box2, funcxy))</tt></dd></dl>
<dl><dt><a name="-Point"><strong>Point</strong></a>(...)</dt><dd><tt><a href="#-Point">Point</a>(x, y)</tt></dd></dl>
<dl><dt><a name="-Value"><strong>Value</strong></a>(...)</dt><dd><tt><a href="#-Value">Value</a>(x)</tt></dd></dl>
<dl><dt><a name="-concatenate"><strong>concatenate</strong></a>(...)</dt><dd><tt><a href="#-concatenate">concatenate</a>((a1, a2, ...), axis=0)<br>
<br>
Join arrays together.<br>
<br>
The tuple of sequences (a1, a2, ...) are joined along the given axis<br>
(default is the first one) into a single numpy array.<br>
<br>
Example:<br>
<br>
>>> <a href="#-concatenate">concatenate</a>( ([0,1,2], [5,6,7]) )<br>
array([0, 1, 2, 5, 6, 7])</tt></dd></dl>
<dl><dt><a name="-delete_masked_points"><strong>delete_masked_points</strong></a>(*args)</dt><dd><tt>Find all masked points in a set of arguments, and return<br>
the arguments with only the unmasked points remaining.<br>
<br>
The overall mask is calculated from any masks that are present.<br>
If a mask is found, any argument that does not have the same<br>
dimensions is left unchanged; therefore the argument list may<br>
include arguments that can take string or array values, for<br>
example.<br>
<br>
Array arguments must have the same length; masked arguments must<br>
be one-dimensional.<br>
<br>
Written as a helper for scatter, but may be more generally<br>
useful.</tt></dd></dl>
<dl><dt><a name="-dot"><strong>dot</strong></a>(...)</dt><dd><tt><a href="#-dot">dot</a>(a,b)<br>
Returns the dot product of a and b for arrays of floating point types.<br>
Like the generic numpy equivalent the product sum is over<br>
the last dimension of a and the second-to-last dimension of b.<br>
NB: The first argument is not conjugated.</tt></dd></dl>
<dl><dt><a name="-makeValue"><strong>makeValue</strong></a>(v)</dt></dl>
</td></tr></table><p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#55aa55">
<td colspan=3 valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"><big><strong>Data</strong></big></font></td></tr>
<tr><td bgcolor="#55aa55"><tt> </tt></td><td> </td>
<td width="100%"><strong>Float</strong> = 'd'<br>
<strong>Float32</strong> = 'f'<br>
<strong>Float64</strong> = 'd'<br>
<strong>IDENTITY</strong> = 0<br>
<strong>Int</strong> = 'l'<br>
<strong>Int16</strong> = 'h'<br>
<strong>Int32</strong> = 'i'<br>
<strong>LOG10</strong> = 1<br>
<strong>POLAR</strong> = 0<br>
<strong>absolute</strong> = <ufunc 'absolute'><br>
<strong>ceil</strong> = <ufunc 'ceil'><br>
<strong>colorConverter</strong> = <matplotlib.colors.ColorConverter instance at 0xb593c52c><br>
<strong>divide</strong> = <ufunc 'divide'><br>
<strong>division</strong> = _Feature((2, 2, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 8192)<br>
<strong>generators</strong> = _Feature((2, 2, 0, 'alpha', 1), (2, 3, 0, 'final', 0), 0)<br>
<strong>lineMarkers</strong> = {0: '_draw_tickleft', 1: '_draw_tickright', 2: '_draw_tickup', 3: '_draw_tickdown', '': '_draw_nothing', ' ': '_draw_nothing', '+': '_draw_plus', ',': '_draw_pixel', '.': '_draw_point', '1': '_draw_tri_down', ...}<br>
<strong>lineStyles</strong> = {'': '_draw_nothing', ' ': '_draw_nothing', '-': '_draw_solid', '--': '_draw_dashed', '-.': '_draw_dash_dot', ':': '_draw_dotted', 'None': '_draw_nothing', 'steps': '_draw_steps'}<br>
<strong>log</strong> = <ufunc 'log'><br>
<strong>log10</strong> = <ufunc 'log10'><br>
<strong>maximum</strong> = <ufunc 'maximum'><br>
<strong>minimum</strong> = <ufunc 'minimum'><br>
<strong>newaxis</strong> = None<br>
<strong>rcParams</strong> = {'axes.axisbelow': False, 'axes.edgecolor': 'k', 'axes.facecolor': 'w', 'axes.formatter.limits': (-7, 7), 'axes.grid': False, 'axes.hold': True, 'axes.labelcolor': 'k', 'axes.labelsize': 12, 'axes.linewidth': 1.0, 'axes.titlesize': 14, ...}<br>
<strong>sqrt</strong> = <ufunc 'sqrt'><br>
<strong>which</strong> = ('numpy', 'rc')</td></tr></table>
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